Editors’ Note

Lan Guan serves as Chief AI Officer for Accenture. In this role, she works closely with companies across industries and geographies to develop data and AI strategies that drive value and growth. Guan brings deep expertise in embedding AI into business processes and transforming data into actionable insights and leads. Guan is a member of the Global Management Committee. Guan also leads the Accenture Center for Advanced AI – the AI epicenter that enables enterprises to capture and create value from their AI investment by leveraging deep expertise, differentiated scalable assets and solutions underpinned by data prowess and industry knowledge, and market-leading thought leadership and research. Prior to this role, Guan was the global leader for Data & AI for Accenture Cloud First, where she focused on transforming data propelled by the Cloud Continuum into actionable plans and scalable solutions to maximize market opportunities for clients. Guan serves on the advisory board of the AI4All, a nonprofit organization dedicated to increasing diversity and inclusion in AI education, research, development, and policy. She is a founding member of the Stanford Institute for Human-Centered Artificial Intelligence (HAI) – an institute dedicated to advancing AI research, education, policy, and practice to improve the human condition – where she established the Accenture Stanford Foundation Model Scholar Program. Guan was listed as one of the Top 25 Consultants and Leaders in AI by The Consulting Report in 2023. She received the Outstanding 50 Asian Americans in Business award in 2023 and was the recipient of the Top Women Leaders in Consulting for 2022. Guan holds an MBA degree in Computational Engineering from the University of Michigan in Ann Arbor, and a PhD ABD in Quantitative Econometrics from Wayne State University. She has been awarded over ten patents in AI-related areas including content recommendations, digital marketing, and sales optimization. Guan is an Adjunct Faculty with The Data Science Institute at Columbia University.

Company Brief

Accenture (accenture.com) is a leading global professional services company that helps the world’s leading businesses, governments, and other organizations build their digital core, optimize their operations, accelerate revenue growth, and enhance citizen services – creating tangible value at speed and scale. Accenture is a talent and innovation led company with 733,000 people serving clients in more than 120 countries. Technology is at the core of change today, and Accenture is one of the world’s leaders in helping drive that change.

What have been the keys to Accenture’s industry leadership?

The depth and breadth of Accenture’s industry expertise is one of our strongest competitive advantages, and this holds true in data and AI as well. The data-driven enterprise is becoming the AI-driven enterprise, but trends, standards and value varies widely from one industry to the next. Our experience has enabled us to design industry-specific solutions that use AI to help companies reinvent themselves and their industries.

How do you describe Accenture’s culture and values?

Accenture has an amazing culture with more than 730,000 talented people across 120 countries, and we’re consistently recognized as a most admired company and a great place to work. In fact, our commitment to our people and culture has been recognized as #1 on the Refinitiv Global Diversity & Inclusion Index for the fourth time in six years. We’ve been on Ethisphere’s World’s Most Ethical Companies list for 16 consecutive years and been ranked #10 among 25 companies on World’s Best Workplaces™ by Fortune and Great Place to Work®.

As a talent- and innovation-led organization, our people have highly specialized skills that help drive our differentiation and competitiveness. We’re committed to a culture of shared success, to investing in our people, to providing them with boundaryless opportunities to learn and grow in their careers through their work experience. Through continued development, training, and reskilling, we help our people achieve their aspirations both professionally and personally. This means fostering a culture and a workplace in which all of our people feel a sense of belonging and are respected and empowered to do their best work. This unwavering commitment to inclusion and diversity starts at the top with Julie Sweet, our chair and CEO. I’m also extremely proud of the fact that Accenture is now 48 percent women with 29 percent women serving as managing directors, showing significant progress on our 2025 goals of gender parity and 30 percent women managing directors.

Will you provide an overview of your role and areas of focus?

I was recently named Accenture’s first Chief AI Officer. This means that I advise clients across industries and geographies on how to use data and AI to drive business value and growth in a responsible way. At Accenture, I’ve built a career out of helping companies turn data into insights and action. Prior to my current role, I led the Data & AI team for Accenture Cloud First, showing clients how modernizing their data in the cloud, and infusing that data with AI, can lead to massive new value.

I have a long history both with Accenture and working in data and AI. My interest in data and AI started when I was a child growing up in China. When I was 16, I built a robot that used data and AI technology to help the other children in my village learn to speak English. That experience showed me the power of technology and how it can be used to improve our lives and communities.

How is Accenture working with clients to develop data and AI strategies that drive value and growth?

AI is a rapidly changing industry, and keeping up with the technology, deploying it responsibly, and finding and upskilling the right talent to support these changes can be incredibly challenging. Our clients are looking at AI from many angles, from strategy and use case implementations to tech enablement, scaling, to model customization, tuning and training, to talent and responsible AI. We work alongside our clients at every step to modernize programs, develop strategic frameworks, and create efficiencies and digitize more quickly, optimize resources and budgets, encourage innovation, and ultimately reinvent their business.

For instance, a large, global oil and gas company came to us wanting to gain more value from the over one million data points the company had collected. With disparate data sources and repositories, technicians and engineers had to comb through pages and pages of historical documents to try and predict when pipeline maintenance or repairs would be needed. We built a generative AI solution that incorporated hundreds of thousands of data points, and summarizes relevant information for user inquiries. It allows users to “chat” with the company’s data to find what they need in a quick and conversational manner, speeding up decision-making and giving people the confidence they need to act.

Will you discuss Accenture’s work in embedding AI into business processes and transforming data into actionable insights and leads?

Accenture has worked with AI for over a decade, across numerous industries and functions. Working alongside our clients, we focus on three pillars of generative AI – data, infrastructure, and people. First, companies need to test and adjust approaches to data privacy, model accuracy, bias and fairness, and learn when “human in the loop” safeguards are necessary.

Next, companies must decide whether they have the right technical infrastructure, architecture, operating model, and governance structure to meet the high compute demands of LLMs and generative AI, while keeping a close eye on cost and sustainable energy consumption.

Finally, take a people-first approach. Success with generative AI requires an equal attention on people and training as it does on technology. Companies should be ramping up investment in talent to address two distinct areas: creating AI and using AI. We’ve taken this approach internally, using AI to create tools that help our people be more productive and add more value. Accenture’s Manage mySales solution, for instance, was developed to bring together sales data from multiple applications to streamline, simplify and integrate the sales management processes from start to finish. We used AI to add in a Win Probability Predictor that exposes positive and negative drivers of predicted win probabilities and shows sales teams how to alter opportunities to win by providing real-time scoring capabilities to sales teams as they work.

When it comes to generative AI, the most important step is to dive in. Companies should be exploring and looking at use cases for generative AI now, because early adopters will turn into fierce competitors.

Will you highlight the Accenture Center for Advanced AI and how you define its mission?

I lead the Accenture Center for Advanced AI – our AI epicenter that enables clients to capture and maximize value from their AI investment by leveraging Accenture’s deep expertise and scalable assets and solutions, all underpinned by research, data prowess and industry knowledge.

Do you feel that there are strong opportunities for women in leadership roles in technology?

It is important to me to create and support opportunities for women in STEM careers. I have a passion for developing and leading programs that address the urgent need for more women in technology, ranging from empowering minority women from immigrant communities with STEM skills to inspiring young women from around the world to innovate.

The prevalence of artificial intelligence and generative AI means the case for more women in technology roles is stronger than ever. Large language models and AI models are only as good as the data they’ve been trained on. We need women involved at every step to help ensure that the data is diverse, that algorithms are inclusive, and models are at a reduced risk for bias.

You devote your time and effort to supporting nonprofits. How do you decide where to focus your efforts?

I support nonprofit organizations that focus on creating opportunities for women to build careers in STEM fields. I serve on the advisory board of the AI4All, a nonprofit organization dedicated to increasing diversity and inclusion in AI education, research, development, and policy. I’m also working with the technology startup community and have brought in several startups to work with Accenture’s FutureofU program, which upskills women with in-demand skills and helps them re-enter the workforce.

What are your priorities for Accenture’s AI efforts as you look to the future?

My priority is to create tangible value from data and AI, not only for businesses, but society and humanity as well. We are helping our clients move from interest to action to value, and in a responsible way. And we are looking to improve individuals and communities. For instance, in our Dublin office, Accenture Labs professionals used clustering and an “embedded knowledge graph” to develop an AI model capable of recommending a personalized exercise plan for any employee.

Another priority is talent. Accenture plans to double its Data & AI workforce to 80,000 people. This means that we have to create multiple pathways to reach that goal. On the upskilling front, we are sending our people through internal training resources and giving options on courses and tracks to follow. We also want to make sure we set up this program so our people, post-training, get on-the-job practical shadowing to learn from the experts. We are also bringing in research scientists and other AI talent through hiring and acquisitions.

Finally, Accenture is committed to encouraging innovation internally and with clients. With extensive research, technology expertise and unique perspectives, we turn trends into real solutions that address our clients’ most pressing business issues.