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### Accenture’s Chief AI Officer Discusses the Significance of This Defining Moment

Accenture’s chief AI officer Lan Guan says there is a lot of work to do to make sure AI is de…

With the emergence of OpenAI’s consumer-oriented verbal program a year ago, artificial intelligence entered the mainstream consciousness. The prominence of AI was one of the most notable narratives of 2023. Businesses worldwide are currently grappling with the challenges of harnessing the potential benefits while mitigating the drawbacks of advanced systems like OpenAI, exemplified by recent leadership turmoil within the organization.

Few individuals possess as deep an insight into these developments as Lan Guan, the Chief AI Officer at Accenture. Accenture, a consulting giant with a workforce exceeding 700,000 and a client base comprising many of the world’s largest corporations, recently announced a substantial $3 billion investment in AI. Lan Guan, a founding member of Stanford’s Institute for Human-Centered AI, has a remarkable background that includes creating an English-language machine for rural Chinese children at the age of 16.

During the annual event hosted by TIME’s partner, Charter, in New York, I had the opportunity to converse with Lan Guan. The dialogue has been condensed and edited as follows:

The recent period has been tumultuous for OpenAI and the economy. What implications does this hold for businesses and the rapid adoption of this technology?

The undeniable value proposition of relational AI necessitates a distinction between the technology and these recent upheavals. Since the inception of ChatGPT, we have witnessed a significant evolution in this market, transitioning from a limited set of modernized solutions to an integrated value chain. The capabilities of generative AI are either currently accessible or soon will be on all major business platforms. The pace of advancements within our client base has accelerated to a matter of months rather than years. This momentum is robust and shows no signs of abating.

How do you practically utilize generative AI technology?

In my personal research endeavors, I have increasingly relied on ChatGPT. Previously, I would frequent Google Scholar to access archived papers for my projects. However, in recent months, ChatGPT has become a valuable resource. For instance, while developing a curriculum on conceptual AI at Accenture, I queried about the prevalent machine learning systems pre-generative AI.

Were you satisfied with the results?

The outcomes exceeded my expectations, leading to success in my endeavors. We extensively leverage relational AI at Accenture for tasks such as summarizing meeting notes and developing proprietary software. Over the past ten months, we have created 300 in-house generative AI applications, streamlining processes like user feedback analysis on various platforms. By training AI to understand our previous work and responses, we have empowered it to generate initial reviews autonomously.

How are clients responding to these advancements? How does this compare to the landscape within Infosys?

Effective implementation largely hinges on knowledge management. The modern business environment thrives on information, yet often underutilizes various data forms. Leveraging relational AI, businesses can extract valuable insights from diverse documents, such as transcriptions of discussions. This capability extends to industries globally, aiding entities like insurance providers in evaluating policy compliance through generative AI.

The advent of ChatGPT last year marked a significant shift. To what extent do these developments reflect a post-ChatGPT era?

While the underlying technology existed previously, its accessibility transformed dramatically with ChatGPT’s introduction. This accessibility has democratized the use of technology, influencing public understanding and its integration into current business practices.

There is a consensus on the urgency of action in response to these advancements. How can organizations navigate this landscape effectively?

Articulating the benefits of investing in generative AI is crucial to overcoming apprehensions and uncertainties among executives. Despite being a nascent field, relational AI is evolving rapidly after years of development, offering transparency and tangible results. Fostering more discussions on this topic can instill confidence within the C-suite and drive progress.

The theme of this session is “Hype vs. Reality.” Do you believe we are in an era of hype, or is this a critical juncture for businesses to adapt or risk obsolescence?

In my view, this is not mere hype but a pivotal moment for numerous industries. Democratizing access to these systems beyond a select few is imperative to ensure widespread adoption and equitable benefits.

As a Chief AI Officer, do you envision a broader role for this position in society?

I believe that every organization should have a Chief AI Officer or an equivalent role to shape the overall AI strategy and drive innovation within the company.

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Last modified: February 19, 2024
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