Book Review: AI First

'AI First: The Playbook for a Future-Proof Business and Brand' by Adam Brotman and Andy Sack (June 2025)

If you were writing a book on the way forward for business in the age of AI, where better to start than picking the brains of tech royalty. How about Sam Altman, Reid Hoffman, Mustafa Suleyman and, why not, Bill Gates. This is exactly what seasoned entrepreneurs and marketers Adam Brotman and Andy Sack have done in their new book, AI First. The result is partly an intellectual pilgrimage through Silicon Valley in search of inspiration. But above all it is an urgent call to action, for you and your business to be AI first. What does this mean? And if AI first, is it people second?

What now?

Businesses everywhere are trying to work out what the hell to do with AI. A few are in the special position of directing the AI weather through their models and infrastructure. A few digital native businesses are built neatly around an AI core. But most, particularly those that are a couple of decades old, are wondering what to do next.

Digital disorientation is nothing new, but there is a sense that successive waves of AI change are swamping the old order - and that things are only just getting started. Generative AI came of age just over 30 months ago. Its precocious offspring are just a few months old - think vibe coding (AI powered software creation) and agentic AI (autonomous AI). The pace is quickening and no business is exempt.

Authors Brotman and Sack, seasoned entrepreneurs with the likes of Starbucks, J.Crew and Microsoft, had their own personal AI epiphany in October 2022. It happened when OpenAI CEO Samuel Altman told them their primary area of business - marketing - like many others would within 5 years be 95% automated by AI.

As a result the book was almost called ‘The Holy Shit moment.’ The authors chose another title. But even if Altman’s predictions prove only partly accurate, how can companies deal with this scale and speed of change?

The reality is most organizations are like the proverbial deer in the headlights. ‘Everyone has a sense of what AI is evolving into. And yet there’s an eerie silence as business leaders look around and wonder what it will mean.’ Brotman and Sack want to help - and enable readers to ‘bridge between the current state of business and an AI future.’

What is AI First?

The phrase ‘AI first’ started to gather momentum in 2024. Google and Microsoft for example used it to reflect the placement of AI at the heart of their product offerings. Similarly a series of CEOs, such as Shopify’s Tobi Lutke, counselled employees to immediately change ways of working and prioritize AI in their key decisions - for example to only hire new employees where they were sure that AI couldn’t do the work. AI should be ‘a baseline expectation of everyone at Shopify.’

For Brotman and Sack AI first is all about urgency. AI should be front and center in planning assumptions, in hiring, in investment decisions, in strategy. It is the opposite of incremental AI, where businesses carry on as usual whilst accumulating cosmetic adjustments to ways of working that barely scratch the surface of the potential for change.

This sense of urgency builds during the course of the book, much of it influenced by the interviews with the industry luminaries noted above. None is more strident than Wharton’s Professor Ethan Mollick: ‘Out of any hundred companies… one really gets it… four have possibly useful projects underway, and the rest are disasters of various types.’ Radical change is essential: ‘if a company isn’t doing this now, they are basically lost.’

To address this, the authors set out two broad recommendations:

• Have an AI first mindset - Leaders and the wider organization need to change their way of thinking. They need to mix the can-do resilience of a ‘growth mindset’ (as popularized by Carol Dweck), the rigor of lean thinking, and a guiding focus on customer requirements. More simply stated it boils down to an alertness and openness to the possibilities of AI.

• Adopt an AI first playbook - With the right mindset, the business can then take concrete steps to build AI into the tasks, workflows and strategies of a business. In particular via:

  • (1) AI education and proficiency - Actively and comprehensively improve AI literacy and proficiency across the organization;

  • (2) An AI council - Set up a cross-functional group with the passion, sponsorship and range of insight needed to make AI successful. Not just tech, but business leaders too;

  • (3) AI policy and governance - Specify guidelines, governance and compliance requirements - without snuffing out experimentation and progress;

  • (4) AI opportunity assessment and road-mapping - Understand in detail which new AI use cases can really make a contribution to efficiency, revenue and growth.

Showing the way

The authors recognize that this broad approach will need careful tailoring for each business. A few may already be AI first, with highly digitized, scalable and AI-friendly operating models (Perplexity fields 2m queries a day with about 40 staff). Others (let’s say a 100 year old steel-maker or a legal services company with 30,000 professionals) will require much more profound change. The key is to get going: ‘Starting now is as much about developing business leaders the mental flexibility they need to figure out how does this apply to me and my business.’

To illustrate, the book shares a range case studies, including for Matt Britton, CEO at market research firm Suzy, and Sal Khan of the Khan Academy . The most detailed case is the pharma company, Moderna. It took the plunge in 2023 with company-wide adoption of ChatGPT Enterprise, a 3000-strong employee AI forum and the corporate mantra ‘act with urgency’. All of this was driven with goals that focused on key customer outcomes (not AI-outcomes) and underpinned with getting the basics right first: ‘there were rooms at Moderna with no plugs… if there’s no electricity, there’s no digital transformation.’ For CEO Stéphane Bancel the most obvious outcome was scalability - Moderna is a company of 5,000+ employees, but with AI it can have the impact of an organization many times the size.

People second?

Critics of AI might at this stage protest. If a key benefit of an AI first approach is to grow a business without expanding its workforce, couldn’t this lead to reduced employment? Wouldn’t low headcount become a new mark of distinction for AI first companies - as suggested when Altman predicted the rise of ‘ten-person, billion-dollar companies.’

This is a very live debate. Since this book was written, the likes of Anthropic’s Dario Amodei have weighed in on AI’s mixed outlook: ‘Cancer is cured, the economy grows 10% a year - and 20% of people don’t have jobs.’

The authors are at pains to point out they are not advocating the displacement of workers. Instead they foresee that jobs will be refocused - for example there will be a new premium on ‘the ability to be a strategic thinker, and to direct, delegate, review and optimize.’ And while ‘some jobs will be replaced… many more will be created.’ Just as in the past when ‘buggy-whip manufacturers went out of business when cars came along.’

The authors conclude ‘we aren’t sugar-coating the level of disruption… but we are choosing to view the glass as half full.’ It is an optimistic outlook, that I subscribe to as well, and our critics will call it complacent. Underemployment could prove to be the ugly brother of AI first thinking.

Get on with it

There is a related question. In a world where talent is scarce and where all companies have been built until now primarily out of human expertise and effort, it is pretty standard to describe a business as ‘people centric’. How can an AI-first business be people-centric as well? How for example can it say that its values, its strategy and ethos are focused on people, when they are focused first on AI? The hope of tech boosters is that people versus AI is a false dichotomy - that there is no choice to make, and that AI will grow productivity and opportunities for employment.

This book dispatches remaining concerns with reference to the customer. Brotman and Sack don’t envisage companies without people, and the mix of people v tech will be determined by what the customer values the most. And if a competitor near you is redefining an industry with AI, then questions about people-centricity or employment are secondary. Or in other words - just get on with it before you go out of business or your skillset becomes obsolete.

The Big Idea: There is a short window of time for companies and individuals to take practical and significant next steps with AI. But time is running out fast: ‘Lean in and embrace the new technology with curiosity and vision… this may be a once-in-a-lifetime opportunity’

This short book packs a lot in and as you’d expect there are many paths that warrant further exploration. I was left wanting to dig more into how AI is redefining key roles, and shaping new ones such as Chief AI Officer; how data fits into the discussion; how AI first impacts the overall structure of an organization, and the role of the IT function; and to explore more the need (raised by Mollick) for each company to set up its own AI lab.

Ultimately the central argument is landed well and AI First provides a strong call to action. The prescription is alertness plus decisive action. The book concludes by saying the clock is ticking. The window for action is closing, with 24 months before obsolescence. Make that 23 months.

Next review - ‘The Thinking Machine: Jensen Huang, Nvidia and the World’s Most Coveted Microchip’ (April 2025), by Stephen Witt

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