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Three roles CEOs need to play to scale Generative AI

Leading a Generative AI-Fueled Enterprise: A CEO series

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About Leading a Generative AI-Fueled Enterprise: A CEO Series

<p>Generative AI remains a high priority for CEOs, and according to our latest Fortune/Deloitte CEO survey, 79% of CEOs surveyed say that accelerating innovation is one of the top use cases for implementing Generative AI.</p><p>With this series of thought leadership pieces, Deloitte aims to help CEOs see ahead into the future to imagine and pursue a GenAI vision that maximizes value for their organizations.</p>

Today’s CEOs must be on the decision-making frontline when it comes to imagining and implementing Generative AI for business success

The strategic opportunities presented by Generative AI require CEOs to dive deep into their organizations’ technology agenda. For many CEOs, that means becoming tech-savvy enough to detect how Generative AI could redefine their business models, including understanding disruptions to their industries, identifying the competitive advantage of AI adoption, and understanding where this advantage could likely erode the fastest.

Given the types of Generative AI choices and their outsized impact, CEOs should dive into key decisions they would normally delegate. They must decide whether to be a first mover or fast follower, whether AI is needed for innovation or productivity, and whether they should be building or buying AI capabilities.

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The buck stops with the CEO

Yesterday’s white-hot innovations can become today’s headaches. Take multicloud for example. Many enterprises rushed into piecemeal cloud agreements without establishing a central decision-making hub, and later found themselves with technical sprawl that desperately needed streamlining. Without caution, Generative AI adoption could take the exact same path.

As more players roll out AI options, CEOs should learn from the lessons of the past and take time upfront to make key decisions, such as:

  • Should we focus our investments on a few key choices, or should we maximize optionality while the competitive market for Generative AI plays out?
  • How can our organization build flexibility in our execution approach?
  • How will we measure direct and indirect cost and performance implications?
  • How do we embed trust and guardrails in the AI model development?

In the context of Generative AI, CEOs must apply their experiences as dealmakers, venture capitalists who bet on winning strategies, and champions of business priorities to three important areas: securing computing power, selecting an ecosystem for their large language models (LLMs), and establishing centers of excellence.

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Secure computing power access

With the widespread adoption of Generative AI, the necessity for swift model training and execution has emerged as a critical business requirement. Conventional compute infrastructure relies on central processing units (CPUs) that handle data sequentially. However, when dealing with LLMs, specialized AI chips are needed to enable massively parallel processing, a crucial element for efficiently processing terabytes of data through algorithms based on Generative AI. Research predicts that the market for specialized chips will be well over US$60 billion in 2024 and climb up to US$120 billion by 2027.

Some organizations’ needs may be met by niche cloud providers who specialize in GPUs. However, CEOs with AI ambitions of pursuing innovation and competitive advantage may want to secure more robust computing power. Many such CEOs are engaged in conversations with Generative AI hardware companies and are negotiating with chipmakers to secure the right level of resources.

As dealmakers, CEOs must consider investor sentiments and engage with their executive leadership team, specifically their chief information officer (CIO) and chief technology officer (CTO), to facilitate alignment between hardware procurement strategies and overarching business objectives. Additionally, emerging technologies such as edge computing present new opportunities for decentralized AI processing. By staying abreast of technological advancements and market trends, CEOs can make informed decisions to future-proof their organization's computing infrastructure.

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Select an AI ecosystem

The value of Generative AI hinges upon the data it consumes. This presents a problem for CEOs, as most LLMs available are not built with out-of-the-box domain, industry, or organization-level specificity. Private LLMs can deliver clear advantages in choice, cost, and control, while enabling enterprises to retain their intellectual property. To capture value and scale, enterprises need to select the LLMs and broader AI ecosystems that suit their specific needs.

CEOs can view their organization’s data as a bargaining chip. This untapped data trove could be highly valuable to companies building AI products. CEOs can consider valuing current and future-state data assets as potential inputs to new models, as long as they concurrently secure or anonymize data to avoid trust and regulatory concerns.

As with securing hardware, the CEO need not delve too deep into the technical specifics of different AI models. Instead, the CEO must calibrate the company’s AI ambition and determine whether it will be a a first mover in building custom LLMs or buy them later. Adopting a venture-capitalist-like mindset, the CEO can leverage understanding of the marketplace and established relationships with major players to determine which bets can be made safely, while considering their broader portfolio and being thoughtful about every round of investment.

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Establish AI centers of excellence

A recent Deloitte and Fortune CEO survey found 80% of organizations are already implementing or likely to implement Generative AI to accelerate innovation, while 96% are doing so to increase efficiencies. To reap these expected benefits, organizations are establishing AI centers of excellence (COEs). These hubs serve as catalysts for innovation, enabling organizations to conceptualize, develop, and deploy AI solutions at scale. A COE can bring together a cross-functional group of AI experts and stakeholders to focus organizational efforts and create a consistent approach to governance and guardrails (e.g., by hiring ethicists).

The CEO’s role in implementing a center of excellence is to champion establishment and provide support and resources to facilitate inception. This includes ensuring critical elements such as hardware, data needs, and governance are sufficiently funded.

The CEO also must engage in winning hearts and minds of all stakeholders, including customers, employees, the board, and society at large. Working with their chief legal or risk officer, CEOs can help ensure that all members of the enterprise feel prepared for what’s on the horizon.

Many employees are fearful of AI transformation and are eager to understand what future jobs and skills may look like. CEOs should foster a culture of AI fluency and innovation and champion a clear purpose for AI adoption, as a matter of supercharging humans (not replacing them).

By leveraging AI centers of excellence as platforms for knowledge exchange and collaboration, CEOs can position their organizations as frontrunners in the race to Generative AI advantage.

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Ever-expanding CEO priorities

The AI revolution is bound to alter CEO roles for the years to come. Already, CEOs have to be more tech-savvy than ever, given how important technology is to competitive advantage and ways of working. As AI becomes even more embedded into knowledge work, the details of AI adoption are expanding out of the tech leader’s domain to become CEO priorities.

This is especially true when AI adoption is still nascent. CEOs can bring their experience to bear on the many macro and micro decisions that will need to be made when a technology is both very new and very impactful. As we continue our series on leading an AI-fueled organization, we’ll delve into more aspects of the CEO’s role in preparing their organizations to pivot to the Generative AI future.

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<p>In the coming articles in this series, we’ll help CEOs navigate these challenges by guiding them through organizational readiness, ecosystem strategy, and leadership imperatives. This series is intended to support CEOs on their AI journeys as their organizations evolve from digital enterprises to intelligent enterprises, and finally, to the autonomous enterprise that is right for them. Don't miss the first article in the series, <a href="" target="_blank">A CEO's guide to envisioning the Generative AI enterprise</a>.</p>

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