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EY and Microsoft announce expanded alliance to help businesses achieve net-zero goals

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End-to-end solutions and platforms

With a focus on decarbonization through solutions such as the EY Decarbonization Management Platform , clients can more clearly understand their current state and manage, monitor and report against it. They gain full visibility of carbon footprints to make sound future decisions and prioritize and monitor the right intervention pathways and investments for their business. The suite of offerings facilitates emissions and offsets data capture, accounting, scenario modeling, risk assessment and external disclosures across asset portfolios and investments. This results in a lower risk transition that will accelerate clients’ sustainability journey, helping them to model ESG strategies and support planning, management and roll-out of end-to-end decarbonization.
Recognizing the complexity and variety of ESG data, EY and Microsoft are building a robust set of solutions unifying data intelligently, leveraging the Structured Data Manager and integrating with Microsoft Sustainability Manager. These solutions support better, more informed decision-making, financial analysis and external reporting for carbon and other critical ESG areas.
Understating how the industry views ESG and sustainability performance requires a set of data intelligence, which is easily delivered with EY ESG IQ . This unique accelerator standardizes and enriches company rating data, calculates score gaps at the most granular level and makes rating improvements faster and easier. This is critical for end-to-end monitoring of supply chains.

Elisabeth Brinton, CVP, Sustainability at Microsoft, says:

“The inherent flexibility of the Microsoft Cloud combined with deep EY sustainability experience and development of business applications will allow clients to rapidly adapt and implement solutions that help them to meet their sustainability goals. This modular solution approach provides a highly scalable platform that utilizes artificial intelligence, machine learning and predictive analysis. This will help clients to meet ESG requirements as they evolve and address them through a life cycle of services for end-to-end decarbonization, transforming their operations to not only reduce their environmental impact and address regulatory requirements but also seize opportunities along the way.”

By leveraging the knowledge and implementation capabilities of cross-functional EY teams and the power of the Microsoft Cloud, clients will be able better to assess and drive enterprise readiness for carbon tracking and traceability opportunities; obtain a clear understanding of both the technology landscape and data emission sources; identify digital opportunities to streamline data processing; evaluate industry standards; and identify opportunities to influence and lead.

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McKinsey and Microsoft join forces to accelerate decarbonization transformations

September 12, 2022 Organizations driving towards net-zero often face a major impediment—the lack of an efficient, scalable technology solution. To calculate their organization’s overall carbon footprint, build a robust decarbonization plan, and execute it with confidence and transparency, leaders need technology that can rival the challenge.

To address this, Microsoft and McKinsey have joined forces to create an integrated solution that combines sustainability data intelligence from Microsoft Sustainability Manager with decarbonization planning and an execution engine using McKinsey Sustainability’s Catalyst Zero . This technological collaboration will enhance companies’ sustainability transformations by integrating their data from activities that produce emissions with initiatives to abate them.

Powered by Microsoft Cloud for Sustainability, this combined solution uses Sustainability Manager to automate and scale the collection of companies’ sustainability-related data and support establishing an emission baseline. Following that, McKinsey’s Catalyst Zero solution, which draws on our sustainability expertise and proven transformation experience, provides a holistic understanding of emissions at company, product and value chain levels, and helps leaders create a detailed decarbonization plan by leveraging a vast proprietary library of decarbonization levers.

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During execution, the ongoing data feed between Microsoft’s and McKinsey’s solutions regularly monitors whether the impact forecasted in the decarbonization plan is happening as planned. This creates confidence in the decarbonization impact achieved and transparency for all stakeholders, including clients, consumers, shareholders, and regulators.

The joint solution is powered with tens of thousands of emission factors and decarbonization levers across 70+ industry sectors to rapidly quantify baseline emissions, generate a company-specific Marginal Abatement Cost Curve (MACC), and finally plan and track granular decarbonization initiatives.

“We are focused on accelerating progress to achieve a more sustainable future, and our collaboration with McKinsey, to deliver innovative Cloud for Sustainability solutions will help customers unify their data intelligence, build robust IT infrastructure and gain insights into their overall carbon footprint in order to help them develop and execute robust decarbonization strategies to achieve their sustainability goals.” says Elisabeth Brinton, Microsoft Corporate Vice President for Sustainability.

Catalyst Zero: Accelerating decarbonization transformations at scale

“Urgent and decisive action to curtail emissions is needed if we are to reach net zero by 2050,” says Tomas Nauclér, senior partner at McKinsey and global co-leader of McKinsey Sustainability. “By combining our tech and sustainability expertise and experience, Microsoft and McKinsey will help businesses accurately and swiftly measure and reduce their overall carbon footprint.”

By combining our tech and sustainability expertise and experience, Microsoft and McKinsey will help businesses accurately and swiftly measure and reduce their overall carbon footprint. Tomas Nauclér, McKinsey senior partner and McKinsey Sustainability global co-leader

Microsoft and McKinsey have a long and successful history of collaborating to accelerate and scale client impact. Over the past three years alone, the two organizations have worked together to help clients de-risk transformations, redesign business processes through data and analytics, and build new digital businesses. These collaborations span across industries and include, for example, a technology transformation for a wireless-equipment manufacturer that achieved a 125 percent increase in output and tripled build speed, or technological innovations for a real estate company to mitigate COVID-19 risk for employees returning to the office.

Our two companies look forward to building on this history of collaboration of proven successes as we enter the next horizon of this alliance.

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Case study: How Microsoft helps its suppliers create and maintain safe working environments

Operating worldwide, developing, licensing and supporting a wide range of software products, services and devices, Microsoft interacts with thousands of suppliers every day. Microsoft’s aim is to make sure that all its suppliers, throughout a supply chain that spans 25 countries around the world, maintain high standards of health and safety.

This case study is based on the 2015 Citizenship Report by Microsoft pu blished on the Global Reporting Initiative Sustainability Disclosure Database that can be found at this link . Through all case studies we aim to demonstrate that CSR/ sustainability reporting done responsibly is achieved by identifying a company’s most important impacts on the environment and stakeholders and by measuring, managing and changing.

Microsoft’s hardware business has grown since its inception in 1982. Today, Microsoft’s Device and Supply Chain Group manages this supply chain, spanning 25 countries across the globe, tryingto help suppliers create and maintain safe working environments. After measuring and setting targets, Microsoft took action to provide training resources for suppliers Tweet This! – Microsoft created a training platform that includes labor, ethics, environmental, health and safety (EH&S) training course modules for suppliers –, work with factory management to build a culture of health and safety, track key health and safety performance indicators and, also, implement a new supplier improvement program.

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Which are the most important impacts (material issues) Microsoft has identified;
How Microsoft proceeded with stakeholder engagement , and
What actions were taken by Microsoft to help its suppliers create and maintain safe working environments

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What are the material issues the company has identified?

In its 2015 Citizenship Report Microsoft identified a range of material issues, such as climate change and energy, data privacy and security, device lifecycle impacts, environmental/social applications of technology, ethical business practices, talent management and development, human rights. Among these, helping its suppliers – across a supply chain that spans 25 countries around the world – create and maintain safe working environments stands out as a key material issue for Microsoft.

Stakeholder engagement in accordance with the GRI Standards

The Global Reporting Initiative (GRI) defines the Principle of Stakeholder Inclusiveness when identifying material issues (or a company’s most important impacts) as follows:

“The organization should identify its stakeholders, and explain how it has responded to their reasonable expectations.”

Stakeholders must be consulted in the process of identifying a company’s most important impacts and their reasonable expectations and interests must be taken into account. This is an important cornerstone for CSR / sustainability reporting done responsibly.

Key stakeholder groups Microsoft engages with:

How stakeholder engagement was made to identify material issues

To inform its decisions, Microsoft regularly communicates with thousands of stakeholders globally ranging from parents concerned about their child’s online safety to international human rights experts. These engagements take many forms. Employees from Microsoft’s business and operational groups regularly identify and engage with stakeholders in the course of their daily work activities. Microsoft’s Citizenship and Public Affairs team also manages a number of stakeholder relationships and ongoing dialogues to help inform and guide the company’s strategies. Microsoft connects with leading thinkers on corporate responsibility and societal challenges in groups such as Business for Social Responsibility, CSR Europe and the World Economic Forum. Microsoft learns from them and other advocacy groups, socially responsible investors, corporate responsibility rating agencies, other external stakeholders and its own employees to identify new and emerging citizenship issues. Microsoft also bases its work on international frameworks such as the United Nations Global Compact, the UN Guiding Principles on Business and Human Rights and the Global Reporting Initiative’s Sustainability Reporting Guidelines.

As regards customers, Microsoft gains insights from online feedback, support communities, product satisfaction surveys, usability studies, research forums, business account managers and the company’s customer service representatives. Regarding investors, beyond traditional investor communications such as earnings calls and Microsoft’s annual meeting, Microsoft seeks to proactively provide investors with corporate governance information through diverse communications, including a director video interview series and direct communications from independent members of its board to shareholders. Microsoft proactively reaches out to institutional investors—including public pension funds and socially responsible investors—about governance and citizenship-related topics and delivers a summary of their feedback to the board. In FY15, these engagements reached investors holding over 40 percent of Microsoft’s outstanding shares. Microsoft seeks to transparently provide information sought by socially responsible investors and corporate responsibility rating agencies and seeks their insights to identify new and emerging citizenship issues.

Microsoft asks for – and acts on – employee feedback in multiple ways, including conducting an annual online anonymous poll of all its employees around the world. The poll, with a nearly 85 percent response rate, asks employees to share feedback about the Microsoft work experience, including how they feel about their workgroups, organization and company as a whole. Microsoft engages with suppliers through capacity-building workshops and trainings, supplier advisory boards, hosting an annual supplier summit and participation in industry coalitions, such as the Electronics Industry Citizenship Coalition. Microsoft also conducts anonymous Voice of the Supplier Surveys, which include questions on citizenship issues.

Microsoft’s local citizenship teams work directly with community groups and in partnerships with local nonprofits. They share views and insights from local communities with Microsoft’s global Citizenship and Public Affairs team in direct communications, through regular conference calls and at an annual global summit. Also, across the breadth of its business, Microsoft engages with thousands of NGOs working on issues ranging from environmental sustainability to employee diversity to child safety.

What actions were taken by Microsoft to help its suppliers create and maintain safe working environments?

In its 2015 Citizenship Report Microsoft set the following targets for helping its suppliers create and maintain safe working environments, based on the company’s approach to materiality – on taking action on what matters, where it matters:

Providing training resources

Microsoft created a training platform called SEA (Social and Environmental Accountability) Academy that includes labor, ethics, environmental, health and safety (EH&S) training course modules for suppliers. In FY15, Microsoft also conducted trainings for 504 trainees from its high-risk suppliers. The courses are also designed as a “train the trainer” with project management training to complement the expert content and provide tools on how to successfully improve their factories.

Working with factory management to build a culture of health and safety

Microsoft worked with factory management to emphasize the need to use competent and experienced EH&S professionals to define and implement the programs necessary to build a culture of health and safety. To address this, Microsoft piloted a number of training modules in its Tier 1 and high-risk Tier 2 suppliers, including: Safety Culture, EH&S Professionals and Senior Management Capability Improvement, EH&S Employee Participation, Risk Behavior Change, EH&S Standardization, Risk Assessment, Chemical Safety and Management, Line Manager EH&S Skills Improvement, Safety Officer Certification for EH&S Staff, Prevention of Occupational Disease, Effective Water Management. In FY15, 528 SEA (Social and Environmental Accountability) professionals from the Microsoft Device Supply Chain attended the company’s SEA in-house training, representing factories with more than 32,000 workers.

Tracking key health and safety performance indicators

Implementing a new supplier improvement program

In FY14, to address the growing need for additional capacity building among some Tier 2 suppliers, Microsoft launched a new program to provide targeted component suppliers with onsite consulting from the SEA program team. Microsoft also continued its program to target its lowest performing component suppliers with special additional inspections that include Microsoft executives as well as SEA and Sourcing team members. This subset of suppliers face an additional compliance scorecard and must improve their performance within a quarter. Additional time may be given in certain occasions that are justified and approved by the SEA team. As a result of the close engagement and collaboration with suppliers to make improvements identified during these audits and assessments, factory and worker conditions have advanced at many of Microsoft’s suppliers. Suppliers who failed to meet the requirements are subject to phase-out and termination of business with Microsoft.

Which GRI indicators/Standards have been addressed?

The GRI indicators/Standards addressed in this case are:

1) G4-12: Describe the organization’s supply chain – the updated GRI Standard is: Disclosure 102-9 Supply chain

2) G4-LA14: Percentage of new suppliers that were screened using labor practices criteria – the updated GRI Standard is: Disclosure 414-1 New suppliers that were screened using social criteria

3) G4-LA15 : Significant actual and potential negative impacts for labor practices in the supply chain and actions taken – the updated GRI Standard is: Disclosure 414 -2 Negative social impacts in the supply chain and actions taken

References:

1) This case study is based on published information by Microsoft, located at the links below. For the sake of readability, we did not use brackets or ellipses. However, we made sure that the extra or missing words did not change the report’s meaning. If you would like to quote these written sources from the original, please revert to the following links:

http://database.globalreporting.org/

https://www.microsoft.com/about/csr/responsible-supply-chain/ (June 2016)

2) http://www.fbrh.co.uk/en/global-reporting-initiative-gri-g4-guidelines-download-page

3) https://g4.globalreporting.org/Pages/default.aspx

4) https://www.globalreporting.org/standards/gri-standards-download-center/

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AI for social impact: 3 ways financial services can influence global challenges

By Bill Borden, Corporate Vice President of Worldwide Financial Services, Microsoft
Azure OpenAI Service
Generative AI
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Customer stories

In virtually every customer conversation I have these days, I am inspired by the innovation that generative AI has ignited in the financial services industry. There’s no shortage of creative ideas and impactful use cases for business transformation—with exciting new capabilities to cut costs, boost efficiencies, enhance productivity, and deliver better customer support.

What is equally if not more important, however, is the power of AI to help solve some of the world’s most challenging social problems. This resonates with the work we’re doing with Microsoft Cloud for Financial Services , where we strive to not only empower customers but also help improve the world broadly through responsible AI and cloud computing.

Microsoft Cloud for Financial Services

Unlock business value and deepen customer relationships.

It’s clear that generative AI opens new doors to create greater value for customers, the benefits of which are already dramatic across industries . In the unique case of financial services, generative AI also opens opportunities to address global problems that have long challenged almost every segment of society.

Three areas of financial services impact

In January, I had the opportunity to participate in the World Economic Forum’s annual meeting in Davos, Switzerland. Naturally, AI was a big topic of conversation, and what was most encouraging to me were the discussions and examples of its potential to impact major social challenges. In the context of social good, I see three key areas where this can happen:

1. Equity and inclusion

I see advanced and generative AI holding tremendous potential to create more inclusive and personalized financial products and experiences for a broader population. This could include the latest natural language capabilities in chatbots, integrating screen reading and narration capabilities like Seeing AI into your banking products for the blind and low vision community, and offering speech-to-text functionality for those with hearing impairments. A powerful example of the transformative potential of AI in coding is the story of Anton Mirhorodchenko , a Ukrainian software developer living with cerebral palsy. By using GitHub Copilot, he dramatically simplified his workflow and improved his productivity and outlook.

2. Poverty and stability

Financial inclusion is also key to stability, as technological innovations unlock new opportunities for data-driven financial tools that can empower a broader range of underserved communities to achieve financial independence. There’s a lot of exciting fintech innovation in this area. For example, CWallet, a fintech company specializing in digital wallet services, is empowering migrant workers in Qatar to access financial services with Microsoft Azure. There are other important fintech initiatives underway in places like Latin America and Kenya using AI and digital innovations to improve lives, reduce poverty, expand access to financial services and credit, and narrow the financial inclusion gap.

And it’s exciting to see how other organizations across industries are already innovating with Azure OpenAI Service to enable inclusive growth with technology. For example, as part of our new ADVANTA(I)GE INDIA initiative and AI skilling efforts, Indian social impact organization, Karya, is using Azure OpenAI to help make technology accessible in under-resourced languages and to more inclusive data—with work that also provides rural citizens with training, fair wages, and education about financial tools to make best use of their earnings.

3. Environment

We all recognize the critical importance of addressing climate change, and this is already an important topic in financial services. But I believe we are just scratching the surface on AI’s potential to tackle common risks and opportunities for environmental, social, and governance (ESG) and sustainability efforts in FSI due to slow manual processes, siloed data, data quality issues, lack of insights, and reporting. Generative AI advancements can aid in synthesizing structured and unstructured data, creating ESG insights and recommendations, and reporting out to stakeholders. I’m also excited to see examples from financial leaders like Emirates NBD transforming sustainability measurement capabilities with Microsoft Sustainability Manager .

When it comes to achieving these ambitions—and countless others where AI can make a major difference—success requires more than just cutting-edge technology. Microsoft believes that meaningful innovation can only happen when organizations also embrace a set of enabling principles that focus on ethics and human factors.

The critical role of responsible AI

The excitement around this next wave of AI is undeniable, but we must wield it responsibly to avoid perpetuating biases or excluding segments of society. At Microsoft, we are committed to helping our customers use our AI products responsibly, sharing our learnings, and building trust-based partnerships.

Microsoft Responsible AI standard

To help financial services organizations realize AI’s potential, Microsoft has published the Responsible AI Standard , developed an Impact Assessments template, and created transparency documents for customers using our Azure OpenAI Service and products like the new Bing to share what we’ve learned. The Microsoft open-source Fairlearn toolkit can also help financial services organizations ensure their AI systems are equitable by identifying biases in data. When our partner EY put it to the test with real-world mortgage adjudication data, it improved the fairness of loan decisions, narrowing gender disparities from 7% to less than 0.5%. From Davos, you can also watch my panel discussion on the responsible deployment of AI in financial services.

How inclusive design and diversity unlock potential

Inclusive design hinges on the vast spectrum of human diversity, gleaning insights from varied perspectives. Microsoft champions design principles that recognize exclusion, learn from diversity, and create universally beneficial solutions. Technology that is designed in this way means better access, less friction, and greater emotional connection with more people.

Our commitment to helping others shift to inclusive solutions is found in our Microsoft Inclusive Design toolkit . The tools create large-scale solutions, such as digital experiences that are more responsive and less biased, and cities that are more accessible. In the financial sector, this translates into products and services designed to meet the needs of as many individuals as possible, regardless of their abilities or circumstances.

Likewise, diversity is a proven catalyst for innovation among technology teams. Studies show that greater diversity can help teams focus more on facts, process those facts more carefully, and generate more creativity and innovation. 1 Ethnically and gender-diverse management teams are more likely to financially outperform in their industry, and companies with more women in leadership positions tend to be more profitable. 2 So, for technology to be truly inclusive, it needs to be built by teams that reflect the diversity of its users.

A mission of empowerment through AI

My transition from the banking industry to Microsoft was driven by the potential for meaningful technological innovation that could create a positive change. Despite the challenges we face, my outlook remains optimistic. I hope this blog has set some ideas in motion for you, and I invite everyone to become involved in efforts to use AI in ways that benefit society broadly.

The Microsoft mission is to empower every individual and organization on the planet to achieve more, and we do that by building technology that we believe will change the world. To accomplish that, we know that we must embrace a set of important responsibilities. Trust, reliability, safety, privacy, security, inclusiveness, transparency, and accountability—these are the foundational principles that have guided our leadership in AI over the past decade. Along with our partners and many other global stakeholders, we invite you to join us on the important journey ahead.

To learn more about our commitment to trustworthy AI and to find further resources, please visit our Empowering responsible AI practices website.

1 Diversity wins. How inclusion matters . McKinsey & Company, May 2020.

2 Why Diverse Teams Are Smarter. David Rock and Heidi Grant, Harvard Business Review, Nov 4, 2016.

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ESG Case Studies

The esg initiative at the wharton school, the environmental, social and governance initiative seeks to advance academic research on esg topics. , we drive innovative research in the field of esg to investigate when, where, and how esg factors impact business value., esg integration in finance, esg integration in strategy, esg and organizational change.

Parnassus Investments and Wells Fargo & Co.: Balancing Morals, Metrics and Materiality

A look at the efforts of Ben Allen, CEO of Parnassus, to invest in Wells Fargo while advancing the financial welfare of the firm’s investors and the ESG values so important to many of them and to the staff of the firm.

Engine No. 1: An ESG Upstart Challenges Fund-Industry Assumptions About Organizing An ETF and Everyone’s Assumptions About Proxy Fights

A look into Engine No. 1’s efforts to combine a new ETF that both met a need in the market for active ownership and satisfied gatekeepers with a hedge fund that occasionally pursued activist campaigns needing the support of the Big Three to succeed.

Striking a Balance Between Valuation and Values: Investment Managers Weigh Whether Investments in a Major Oil Company and an Ethanol Producer Serve their Dual Mandate

A look at the decisions Michelle Dunstan and Jeremy Taylor, co-managers of the Alliance Bernstein Global ESG Improvers Strategy, had to make in their effort to buy stocks they believed had the best chance to deliver excellent long-term financial results and improve their ESG performance.

Calculating the Net Present Value of Sustainability Initiatives at Newmont’s Ahafo Mine in Ghana

This case study examines the value and strategy of estimating the net present value of sustainability at Newmont’s Ahafo Mine in Ghana.

Choppies’ Waters: Retailing in Botswana and Sub-Saharan Africa

This case study looks at the impact of Choppies, under the guidance of CEO Ramachandran (“Ram”) Ottapathu, on Botswana and Sub-Saharan Africa.

Designing and Implementing an Integrated Project Management System at Minas-Rio

This case study examines the design and implementation of an Integrated Project Management System to achieve the ultimate goal of First Ore on Ship (FOOS) by November 30, 2014, by Paulo Castellari, CEO of the Anglo American subsidiary Iron Ore Brazil.

Glenmede: How to Credibly Bring an ESG Lens to Investing and Secure Buy-in from Analysts and Clients

A look at Amy Wilson’s efforts to direct ESG investing within the Glenmede Investment Firm credibly and effectively.

Abraaj Group’s Integration of ESG Policies into the Turnaround of K-Electric

This case study explores the efficacy of the Abraaj Group’s strategy in changing the K-Electric company’s direction, with the aim of transforming it into a sustainable, growth-oriented, private sector utility.

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Kerovka simulation

The Kerovka simulation is a highly innovative software tool that is used as part of an organised workshop, either in a classroom or in remote format, to deliver an intense experience that helps participants with a wide variety of experience levels to develop skills for dealing with challenges such as managing crisis scenarios, and leading responsibly & sustainably.

About the Environmental, Social and Governance Initiative

The Environmental, Social and Governance Initiative conducts academically rigorous and practically relevant research with industry partners and across all Wharton departments that investigates when, where, and how ESG factors impact business value. Informed by research, we offer 30+ courses that MBA and undergraduate students can assemble into a major or concentration, over a dozen co-curricular experiences, and three Executive certificate programs. Led by Vice Dean Witold Henisz, the ESG Initiative advances Wharton’s best-in-class education of current and future leaders, enabling them to serve a world undergoing tremendous change.

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ESG in Action: Case Studies of Companies Making a Difference

Discover how companies like Patagonia, Microsoft, and Tesla are making a difference through their ESG initiatives. Learn about the benefits of ESG, common implementation challenges, and how Vakilsearch can help.

Environmental, social, and governance (ESG) considerations have become increasingly important for companies as they seek to build sustainable business models and create long-term value for their stakeholders. Many companies are taking proactive steps to integrate ESG principles into their decision-making processes, and the results are impressive. In this blog, we will explore some case studies of companies that are making a difference through their ESG initiatives.

Table of Contents

Case Study 1: Patagonia’s Sustainable Supply Chain

Patagonia, a popular outdoor clothing and gear brand, has made sustainability a core part of its business strategy. The company has implemented a range of initiatives to reduce its environmental impact, including using organic cotton, recycled polyester, and responsible down in its products. Patagonia has also developed a sustainable supply chain, working closely with its suppliers to ensure that they meet strict environmental and social standards. As a result, Patagonia has been able to reduce its carbon footprint, improve the lives of workers in its supply chain, and create a loyal customer base that values sustainability.

Case Study 2: Microsoft’s Carbon Negative Pledge

Microsoft, a leading technology company, has set an ambitious goal to be carbon negative by 2030. This means that the company will remove more carbon from the atmosphere than it emits. Microsoft has developed a comprehensive plan to achieve this goal, which includes investing in renewable energy, improving energy efficiency, and developing new technologies to reduce carbon emissions. The company has also committed to offsetting all of its historical carbon emissions by 2050. By taking these steps, Microsoft is demonstrating its commitment to sustainability and setting a high bar for other companies in the technology sector.

Case Study 3: Unilever’s Sustainable Living Plan

Unilever, a global consumer goods company, has developed a Sustainable Living Plan that aims to improve the health and well-being of people and the planet. The plan includes ambitious targets to reduce the environmental impact of Unilever’s products, improve the lives of workers in its supply chain, and promote sustainable agriculture. Unilever has also taken steps to increase transparency and accountability by publishing regular reports on its progress towards these targets. By implementing the Sustainable Living Plan, Unilever is showing that sustainable business practices can create long-term value for both the company and its stakeholders.

Case Study 4: Tesla’s Electric Vehicles

Tesla, a leading electric vehicle manufacturer, is driving the transition to a more sustainable transportation system. The company has developed a range of electric vehicles that are designed to be more energy-efficient and environmentally friendly than traditional gasoline-powered cars. Tesla has also invested in developing a network of charging stations to make it easier for people to drive electric vehicles. By offering a compelling alternative to traditional cars, Tesla is helping to reduce carbon emissions and create a cleaner, more sustainable future.

Case Study 5: Starbucks’ Ethical Sourcing

Starbucks, a global coffee company, has made ethical sourcing a top priority. The company works closely with farmers and suppliers to ensure that its coffee is produced in a way that is environmentally and socially responsible. Starbucks has also developed programs to improve the lives of coffee farmers, including providing access to credit and technical assistance. By promoting sustainable agriculture and supporting local communities, Starbucks is demonstrating its commitment to responsible business practices.

Case Studies of Companies Making a Difference with ESG: Challenges of ESG Implementation

Implementing ESG initiatives can present various challenges for companies. Here are four of the most common challenges that businesses may face when trying to implement ESG strategies:

Cost: Implementing ESG initiatives can be costly, especially for small and medium-sized businesses. There may be significant upfront expenses for things like implementing sustainable technology, conducting impact assessments, and training employees on new practices. However, companies that successfully implement ESG strategies often find that the long-term benefits outweigh the initial costs.
Lack of Knowledge and Expertise: Implementing ESG strategies requires specialised knowledge and expertise. Many companies may lack the in-house expertise needed to develop and implement effective ESG strategies, such as conducting environmental impact assessments or setting up sustainable supply chains. To overcome this challenge, companies may need to hire outside experts, collaborate with other organisations, or invest in training for their employees.
Resistance from Stakeholders: Implementing ESG initiatives may encounter resistance from various stakeholders, including investors, customers, suppliers, and employees. Some stakeholders may not fully understand the importance of ESG or may be resistant to change. It’s essential for companies to communicate the benefits of ESG initiatives and involve stakeholders in the planning process to address these challenges.
Measuring Impact: Measuring the impact of ESG initiatives can be challenging. Companies must develop appropriate metrics and methods for measuring the impact of their ESG initiatives. This involves collecting and analysing data to assess the effectiveness of their initiatives and make improvements where necessary. Companies that can effectively measure the impact of their ESG strategies can use this data to report on their progress and improve their strategies over time.

These case studies demonstrate that ESG considerations can create significant value for companies and their stakeholders. Patagonia, Microsoft, Unilever, Tesla, and Starbucks are just a few examples of companies that are making a difference through their ESG initiatives. By prioritising sustainability, social responsibility, and ethical business practices, these companies are building strong reputations, attracting top talent, and positioning themselves for long-term success in a rapidly changing business environment.

As a leading legal and compliance services provider, Vakilsearch can assist companies in their ESG journey by providing legal counsel and compliance guidance, helping them develop and implement effective ESG strategies, and ensuring regulatory compliance. Vakilsearch’s team of experts can help companies navigate the legal and regulatory landscape related to ESG, enabling them to achieve their goals while minimising risks and costs. With Vakilsearch’s support, companies can successfully implement ESG initiatives that create significant value for their stakeholders and position themselves for long-term success.

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MICROSOFT TREASURY: A TWENTY-YEAR PARTNERSHIP FORGED ON INNOVATION & GROWTH

The business.

The Microsoft Treasury group serves as a nerve center for operations in over 190 countries and invests over $120 billion (as of 2021) in cash instruments, fixed income, equity, and other investments. The group monitors thousands of bank accounts and provides just-in-time cash management globally. This mandate requires Microsoft Treasury to rely on a vast amount of data to make fast, accurate and well-informed decisions.

The Challenge

Making well-informed cash management decisions while prioritizing their corporate goals of capital preservation and liquidity was challenging when the team’s infrastructure consisted of spreadsheets, decentralized reporting tools, and manual processes. The challenge and opportunity was to streamline this infrastructure, empowering Microsoft Treasury to act with clarity.

The Solution

Microsoft Treasury’s implementation of the Aladdin® Enterprise platform has streamlined its operations, automated processes, and centralized investment data, allowing the team to efficiently manage multi-asset portfolios within one flexible end-to-end solution. Aladdin has provided Microsoft Treasury with the needed software and services to diversify its portfolios, leading to continued growth over the past 20 years.

ADOPTING ALADDIN – A TRUE END-TO-END OPERATING SYSTEM

In 2002, Microsoft Treasury embarked on a digital journey to transform its business and bring efficiency to new levels. Integrating all investment tools onto one platform, centralizing data, and automating processes have helped Microsoft Treasury manage its multi-asset portfolios.

The end-to-end operating system combines sophisticated risk analytics with comprehensive portfolio management, trading, operations, and compliance tools, providing the group with greater clarity on opportunities and risks in the moment and in the future across its diversified portfolio, all in one place. As the group’s language of portfolios, the platform is used across different Microsoft Treasury teams, enhancing communication and reducing operational risk.

This holistic view of Microsoft Treasury’s portfolio, supported by Aladdin, has enabled the firm to unlock new opportunities and grow its business over the past 20 years.

Across the board, the Microsoft Treasury group found that Aladdin allowed them to access and utilize data easily, helping them see, understand, and act on business opportunities and risks.

Leveraging the industry’s best practices.

Over the last 20 years, Aladdin has helped Microsoft Treasury stay up to date with evolving industry requirements and trends. During the 2008 financial crisis, centralized data allowed the team to quickly aggregate exposures to different banks and make well-informed decisions. Additionally, Aladdin offers regular updates and controls to help stay ahead of key standards such as Current Expected Credit Loss (CECL) regulatory reporting. What-if functionality, for example, helps keep portfolios within compliance limits while having the latest regulatory requirements or accounting standards built into the system makes compliance easier and lets the team focus on more value-added tasks.

FROM COMPLEX TO ACTIONABLE PORTFOLIO INSIGHTS

Microsoft Treasury was able to centralize and efficiently harness its data for portfolio construction, analysis and reporting. With simplified data access, data processing and handling are more seamless. The team can now pull historical data sets, build specific reports, and perform advanced analysis to gain enhanced insights and clarity into its investments. As a result, they can efficiently track investments, optimize portfolio construction, and rebalance portfolios when needed.

UNLOCKING OPPORTUNITIES FOR SCALE

The possibility to onboard different asset classes and standardize the processes of each within Aladdin has supported Microsoft Treasury through various investment policy changes. This capability has allowed the group to bring more of its investments in-house and manage multi-asset portfolios on a single platform, contributing to Microsoft Treasury’s diversification and the scaling of its business over the past 20 years.

Our Treasury investments process has evolved over time and the size and complexity of our portfolio has changed significantly since we first started using Aladdin. We expanded the scope of our investments beyond traditional short-term fixed income, and using the Aladdin platform provided us with the tools and reporting capabilities to manage a multi-asset portfolio.

FUTURE-PROOFING THROUGH PARTNERSHIP

The partnership between Microsoft Treasury and Aladdin has only grown after two decades of collaboration. As Microsoft Treasury’s needs change to keep up with evolving industry trends, Aladdin continually supports the team to stay ahead in key focus areas.

To achieve its sustainability goals, Microsoft Treasury looks forward to unlocking even more value with the platform’s access to headline ESG metrics from industry-leading ESG data providers as the team shifts towards building more sustainable portfolios.

Beyond those ESG-specific portfolios, we want to look at existing portfolios through an ESG lens and see how external managers are contributing to our ESG efforts.

Additionally, the Microsoft and Aladdin teams have recently embarked on a strategic partnership to migrate Aladdin Enterprise to the Microsoft Azure cloud platform, a venture that is key to further enhancing the Aladdin client experience.

Hosting Aladdin infrastructure on Microsoft Azure helps drive more innovation and unlock new capabilities to provide best-in-class features and functionalities. In addition, Microsoft Azure’s network of global data centers and capabilities helps meet the localized needs of Aladdin clients and maintain the platform’s high standards for resiliency and security.

As the first client to migrate its Aladdin platform to Azure, the Microsoft Treasury team reported a smooth transition with no disruption to its operations during the process.

At a high level, integrating our data across platforms is key to unlocking the real value-add. For instance, the continued digital transformation journey that we’re on will pool data for better insights. There are a ton of great opportunities that can come out of this journey together.

Get in touch to learn more about Aladdin

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Aladdin® and eFront® platforms bring together public and private asset class data to create an industry-recognized whole portfolio solution for investment professionals globally. Find out more at www.blackrock.com/aladdin | [email protected]

This material is provided for informational purposes only and is not intended to be relied upon as a forecast, research or investment advice, and is not a recommendation, offer or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed are subject to change at any time without notice. The information and opinions contained in this material are derived from proprietary and nonproprietary sources deemed by BlackRock to be reliable, are not necessarily all-inclusive and are not guaranteed as to accuracy. Performance and risk calculations, including those incorporated into Aladdin technology, are based on assumptions, historical correlations, and other factors (such as inputs provided by the Aladdin users) and are not assured to predict future results. All graphs and screenshots are for illustrative purposes only. BlackRock’s Aladdin platform is a financial technology platform designed for institutional, wholesale, qualified, and professional investor/client use only and is not intended for end investor use. Aladdin users undertake sole responsibility and liability for investment or other decisions related to the technology’s calculations and for compliance with applicable laws and regulations. The technology should not be viewed or construed by any Aladdin users, or their customers or clients, as providing investment advice or investment recommendations to any parties. For additional information on any of the descriptions contained herein, please contact your Aladdin Relationship Management representative. BlackRock may modify or discontinue any functionality or service component described herein at any time without prior advance notice to you.

Certain Aladdin technology products and services may not be offered by BlackRock in your local jurisdiction.

In the U.S. and Canada , this material is intended for institutional investors. In the UK , this material is for professional clients (as defined by the Financial Conduct Authority or MiFID Rules) and qualified investors only and should not be relied upon by any other persons. Please refer to the Financial Conduct Authority website for a list of authorised activities conducted by BlackRock. In the EEA , this material is for professional clients, professional investors, qualified clients and qualified investors. For qualified investors in Switzerland: This information is marketing material. This material shall be exclusively made available to, and directed at, qualified investors as defined in Article 10 (3) of the CISA of 23 June 2006, as amended, at the exclusion of qualified investors with an opting-out pursuant to Art. 5 (1) of the Swiss Federal Act on Financial Services ("FinSA"). 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Please note that by receiving these materials, it shall be construed as a representation by the receiver that it is an Institutional or Qualified investor as defined under Mexican law. BlackRock México Operadora, S.A. de C.V., Sociedad Operadora de Fondos de Inversión (“ BlackRock México Operadora ”) is a Mexican subsidiary of BlackRock, Inc., authorized by the CNBV as a Mutual Fund Manager (Operadora de Fondos), and as such, authorized to manage Mexican mutual funds, ETFs and provide Investment Services. For more information on the Investment Services offered by BlackRock Mexico, please review our Investment Services Guide available in www.blackrock.com/mx . 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Please refer to the Financial Conduct Authority website for a list of authorised activities conducted by BlackRock. Please be advised that BlackRock Investment Management (UK) Limited is an authorised Financial Services provider with the South African Financial Services Conduct Authority, FSP No. 43288.

The SEC's Landmark Climate Disclosure rule is official! Explore the impact on your company

Sustainable Compliance: How Protingent Met Microsoft’s GHG Emissions Reporting Requirements with Good.Lab

Protingent needed an experienced solution partner with climate expertise and the right tools to streamline their emissions management processes.

Industry IT & Engineering Staffing Services
ESG Goals GHG Emissions Calculation & Reporting

Protingent needed an experienced solution partner with climate expertise and the right tools to streamline their emissions management processes . With a pragmatic approach, in- house experts, and scalable software solutions, Good.Lab proved to be the right partner to support Protingent in producing an accurate GHG emissions baseline across Scopes 1, 2, and 3, calculating their service level emissions, and providing guidance in setting targets for emissions reduction to comply with Microsoft’s requirements.

Protingent engaged Good.Lab to meet Microsoft’s supplier requirements to calculate the company’s GHG baseline and service level emissions and explore opportunities to reduce their emissions. As a result of their engagement, Protingent gained access to powerful ESG software tools and experienced climate consultants who guided their journey through GHG Emissions Footprint measurement on to reporting directly to Microsoft. Accordingly, they were able to submit accurate GHG emissions data to comply with Microsoft’s Supplier Code of Conduct and maintain a healthy business relationship.

Good.Lab has been instrumental in guiding Protingent through complying with Microsoft’s supplier code of conduct, particularly in meeting the complex emissions reporting requirement. Their expertise and support have enabled us to accurately measure, track, and report on our carbon footprint, reinforcing our commitment to sustainability. I look forward to a continued relationship with Good.Lab as our sustainability partner. Tim Bruce, CEO & President, Protingent

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A programmer uses a computer to write code to develop network security and enhance product safety.

AI + Machine Learning , Azure Compute , Azure Operator Nexus , Partners , Thought leadership

Empowering operators through generative AI technologies with Azure for Operators

By Victor Bahl Technical Fellow and Chief Technology Officer, Azure for Operators

Posted on April 8, 2024 8 min read

Tag: Azure for Operators
Tag: Copilot
Tag: Generative AI
Tag: Microsoft Intelligent Data Platform

OpenAI’s offerings—ChatGPT, Codex, Sora, and DALL-E—have caught the public’s imagination and opened doors to many opportunities for infusing AI into networks, systems, services, and applications. These cutting-edge AI technologies are now deeply integrated with Microsoft products including Bing, Windows, Office, and Microsoft Teams. Within Azure for Operators , we are taking advantage of the significant investments Microsoft has made and its expertise in programming foundation models by developing technical solutions that will give our customers a competitive advantage. Our product portfolio, which includes Azure Operator Nexus, Azure Operator Insights, and Azure private multi-access edge compute is being augmented with generative AI technologies, empowering operators to efficiently solve real-world problems. But before we get into the solutions, let’s begin with a brief background on generative AI and recent AI advancements.

Azure for Operators

Get to know the Microsoft portfolio for operators

Foundation models and the next era of ai

Background on generative AI

OpenAI’s generative models have drawn significant attention for their exceptional performance in generating text, image, video, and code. Among these generative models, a notable breakthrough is generative pre-trained transformer (GPT), a large language model with hundreds of billions of parameters. GPT is pre-trained on a vast corpus of data from the open internet, allowing it to comprehend natural language and generate human-like responses to input prompts from users. ChatGPT , Codex (the model behind GitHub Copilot), Sora , and DALL-E are all derived from the pre-trained GPT (or foundation model). Codex is additionally trained on code from 54 million GitHub repositories—a process known as “fine-tuning.” To enable the customization of GPT for new language tasks, OpenAI offers a paid API service that allows developers to fine-tune GPT on domain-specific data through a command-line interface and query the fine-tuned model without accessing the underlying model. Through a partnership with OpenAI, Microsoft benefits from exclusive access to the underlying model and parameters of GPT, placing us in a strong position to develop inference and a fine-tuning infrastructure.

Microsoft and openai exclusively license gpt-3

We have divided our AI and machine learning investments into four categories:

Reactive management : Automated incident management.
Proactive management : Automated anomaly detection and fault localization.
AI and machine learning infused into Azure for Operators products.
AI and machine learning engineering platform across Azure for Operators.

I want to talk a little about our investments that fall under the first two categories. These systems showcase the potential of foundation models as they are incorporated into our products, and they can significantly impact the way mobile operator networks are developed, operated, and managed.

Reactive management: Data intelligence copilot for operators

Operators gather vast amounts of data, including node-level, gNodeB-level, user-level, and flow-level data, for purposes like network monitoring, performance tracking, capacity management, and debugging. In commercial operator networks, the number of such counters and metrics that are regularly computed often exceeds several thousands, accounting for tens of Gbps of data transfer. Retrieving relevant metrics and visualizing them is crucial for network operations. However, the complexity of modern wireless systems and the vast number of counters involved make this task challenging, necessitating expert knowledge to perform this essential operation.

The process today involves specialists with expert knowledge creating dashboards for a limited number of metrics, which the operators browse through to obtain relevant information. However, if operators require customized data, such as visualizing throughput for a specific user rather than aggregate throughput or if they need access to a different set of metrics for complex debugging purposes, a loop through the specialists is required. The specialists need to identify the relevant variables, write code in database query language to combine them in an appropriate manner, and then create and share a dashboard.

Can operators interact with their data by asking simple questions in natural language, without having to remember any of the complex counter names or how to combine them in a database query language ?

We believe that such a system has the potential to significantly transform the status quo. It would provide a more natural way to interact with operator data without heavy reliance on specialists. This would reduce the time to mitigate network issues, and it would provide more value from the operator data by reducing the barrier to customized insights.

The development of foundation models like GPT-4 has significantly advanced the capabilities of natural language interfaces for data interaction, demonstrating remarkable performance on standard text-to-SQL datasets. Despite these achievements, challenges persist in specialized and niche domains such as operator data. These challenges include the handling of specialized information that is often not publicly available, the overwhelming volume of data counters and metrics that exceeds the prompt size limits of these models, and the need for numerical accuracy that is crucial for decision-making in network operations but which the foundation models are not adept at.

System architecture for Data Intelligence Copilot for Operators

We have developed data intelligence copilot for operators, a natural language interface for retrieval and analytics tasks on operator data, leveraging foundation models. It addresses the challenges posed by operator data through a combination of a domain-specific database with comprehensive metrics descriptions, a semantic search for filtering relevant metrics within the models’ prompt size limits, few-shot learning for enhancing numerical accuracy in code generation, and expert feedback mechanisms that allow for continuous improvement of the database through contributions from domain experts. 1 This copilot is being integrated into our Azure Operator Insights product as a knowledge assistant.

Reactive management: Intent-based network management

Generally, operator networks are very complex with management operations, heavily relying on highly skilled professionals and sophisticated management tools to create, update, and deploy network configurations. Configuration files can be several tens of thousands of lines long. This process is not only labor-intensive but also error-prone, underscoring a need for automation to alleviate the management burden for network operators.

We have been working on a promising paradigm called intent-based networking (IBN), a solution to simplify network management for operators. It allows network operators to specify the desired behavior or “intent” of their network in natural language. They can say, “ Allow ICMP traffic in my network ,” and then the solution automatically translates the intent into updated network configurations. IBN can present these updated configurations to network administrators for review prior to their deployment, ensuring network safety while keeping minimal human intervention.

Intent-based networking agent powered by GPT simplifies network management.

Although the concept of IBN has been around for some time, its implementation has been hindered by the complexities of natural language understanding and the intricate task of configuration generation. Motivated by recent advances in generative AI (for example GPT), we revisited this problem and developed a tool named “IBN agent” based on GPT. Our IBN agent takes as input the running network configuration and the user’s natural language intent. It then queries GPT to update the network configuration according to the user intent. Utilizing existing configuration syntax checks and network verification tools, the IBN agent also flags errors in the GPT-generated configurations. Moreover, users can intervene at any point and provide feedback on any undesired behavior. Based on these identified errors or user feedback, the IBN agent iteratively refines the configuration with GPT until all automated and human checks are passed. We believe that IBN holds substantial potential to simplify network configuration in the future.

Proactive maintenance: Next generation communications copilot for operators

Practitioners, engineers, researchers, and students can find themselves grappling with a multitude of acronyms and intricate terminology with information spread across many documents, which makes working with and developing standards-compliant systems an onerous and time-consuming task. For example, an engineering team working on implementing a registration request procedure as a part of building 5G virtual core would need to identify all the relevant technical specifications from among thousands of documents and understand the call flow and message formats as described in those specifications.

The current method of acquiring this information involves sifting through numerous webpages and technical specification documents. While this approach provides extensive comprehension of a topic from various sources, it can also be time-intensive and tedious to identify, gather, and synthesize information from multiple relevant sources.

Foundation models represent a significant advancement in providing synthesized, readily comprehensible answers to user queries related to wireless communication specifications. However, despite the usefulness of state-of-the-art large language models, they also produce irrelevant or inaccurate responses to many queries related to niche and specialized domains.

We have developed a conversational AI tool for information synthesis of wireless communication specifications.

Like ChatGPT, the nextgen communications (NGC) copilot offers a question-and-answer interface, but with an enhanced ability to provide more accurate and relevant answers on topics pertaining to wireless communication technical specifications. NGC copilot builds on foundation models, prompt engineering, and retrieval augmented generation approaches; it features a domain-specific database, tailored word embeddings, and a user feedback mechanism. For more accurate responses, it integrates into its database technical specifications and standards that are often overlooked by traditional models due to their niche nature. The system uses a specialized word-embedding model to better understand telecom jargon, improving its query response relevance. Experts can also provide feedback, which helps refine the database and improve answer quality. We have been piloting NGC within our engineering teams and its performance has been excellent.

Proactive management: Network configuration anomaly detection

One of the most common causes of network disruptions today is network configuration errors. Configuration governs the protocols and policies that regulate and control network access, performance, security, billing, and more. Misconfigurations, when they occur, can lead to a frustrating user experience with slow performance, lack of connectivity, or even sweeping service outages. Operators who experience such outages often suffer from loss of reputation and revenue.

Despite the importance of correct network configuration, configuration management today remains a challenge for operators. Manual peer review of configuration changes can have limited effectiveness. Device configurations are often low-level, complex, and long—making them notoriously challenging to audit manually and at scale. On the other hand, automation is also not a panacea; it’s prone to errors, bugs, and mistakes.

The configuration anomaly detection analysis pipeline

Many configuration errors are obvious in hindsight and could be detected by sufficiently intelligent learning models. For this reason, we have invested in developing AI-driven anomaly-detection tools that can proactively identify and block erroneous configuration changes before they are applied to the network—before they can impact real users. Machine learning is adept at identifying common configuration usage patterns and anti-patterns. It can effectively sift through changes to ignore those that are intentional and alert operators about those that are likely unintentional or erroneous.

Given a collection of similar configuration files (such as JSON, XML, or YAML), our system synthesizes a common template that captures the similarities between these configurations, leaving placeholders for differing values. Using the synthesized template, our system employs a state-of-the-art, unsupervised anomaly-detection technique, known as the isolation forest, to pinpoint likely errors in configurations. These potential anomalies are reported with an anomaly-likelihood score for review. In this way, we aim to help operators with safe and reliable management of their 5G networks by leveraging automated validation of configurations. For real-world scenarios and additional technical details, please read our recent paper. 2

Microsoft responsible AI

empowering responsible ai practices

We realize that AI and machine learning-based solutions may involve ethical concerns regarding the underlying models, their training data, and associated biases. To address these concerns, the office of responsible AI shepherds the AI projects at Microsoft on risk assessment and mitigation. We work hard to understand the aspects that require improvement regarding bias and discrimination, and we strive to receive broad approval on compliance. We pass on all guidelines to the engineers to ensure responsible usage without slowing progress.

Explore the Microsoft portfolio of products

My hope is that these examples show that foundation models significantly enhance the Azure for Operators portfolio of products. There is a lot more to say, and there are many additional examples of systems we have developed, but I will leave that for another time.

1 Microsoft, Adapting Foundation Models for Operator Data Analytics, Manikata Kotaru, HotNets 2023 .

2 Microsoft, Diffy: Data-Driven Bug Finding for Configurations, Siva Kesava Reddy Kakarla, Francis Y. Yan, and Ryan Beckett, April 2024 .

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Customer Case Study: Cognizant & Microsoft Collaborate to Power Healthcare with Generative AI

Sophia Lagerkrans-Pandey

April 9th, 2024 0 0

Cognizant and Microsoft Collaborate to Power the Future of Healthcare Administration with Generative AI

Check out the entire Cognizant customer story here discussing how they use Microsoft and Semantic Kernel.

Cognizant and Microsoft are collaborating to infuse generative AI into healthcare administration. This new, groundbreaking collaboration aims to increase productivity and efficiency for healthcare payers and providers, while ensuring timely responses and improved care for patients. The TriZetto Assistant on Facets will leverage Azure OpenAI Service and Semantic Kernel to provide access to generative AI within the TriZetto user interface.

“Generative AI has the potential to inject $1 trillion into the U.S. economy over the next decade through new revenue streams, operational efficiency and innovation in products, services and ways of working,” said Surya Gummadi, EVP and President, Cognizant Americas. “At Cognizant, we’re working closely with clients to understand and implement generative AI into their organizations, helping them unlock and expand value across the enterprise. Through this collaboration with Microsoft, we have infused generative AI capabilities into our TriZetto platform, making it easier for healthcare organizations to realize the full potential of this groundbreaking technology.”

Cognizant’s TriZetto software platform, powered by Microsoft Azure, is a critical tool that can help healthcare payer and provider clients reduce hidden costs and enable better patient outcomes for millions of Americans. Key benefits include:

Access to innovation and data insights
Process automation
Improved regulatory compliance
Enhanced data security

The TriZetto Assistant on Facets complements human users by sourcing enterprise data and summarizing and enriching content. By accessing TriZetto application programming interfaces, this new solution will take actions on behalf of the user and enable desktop automation to further reduce manual steps in workflow. Automating these processes can enable enhanced user experiences, increase efficiencies, and help improve cost containment at scale. For example, by contextualizing desk-level procedures for the transaction at hand, instructions and micro-automations are simplified to improve accuracy and reduce processing time.

Additionally, to improve the accuracy of configurations, generative AI can interpret configuration documents and provide pre-built configuration templates to provide “jump-starts” to user workflows. With appropriate User Identity Management, TriZetto software users will have access to necessary data in several contexts, further extending the value of pre-existing TriZetto and Microsoft investments while preserving access controls, auditability, and producing a higher accuracy of results.

“Generative AI is having a profound and transformational impact on every industry, including healthcare,” said Rob Dahdah, CVP of Microsoft’s Healthcare & Life Sciences Industry and Partner Sales organization. “Working in close partnership with Cognizant, we are building state-of-the art solutions that alleviate the acute challenges facing providers and insurance companies, while also delivering better patient and member experiences. With that same focus on outcomes-based innovation, we are creating productivity tools, interoperability functionalities, and efficiencies of scale that support healthcare organizations to connect across the broader health and life sciences ecosystems.”

Please reach out if you have any questions or feedback through our Semantic Kernel GitHub Discussion Channel . We look forward to hearing from you! We would also love your support, if you’ve enjoyed using Semantic Kernel, give us a star on GitHub .

Cognizant and Semantic Kernel

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