From AI hype to business value: our takeaways from Ann Hiatt’s talk at the Astorg AGM

At this year’s Astorg AGM, we had the opportunity to hear from Ann Hiatt, a leadership strategist, author and former right hand to Jeff Bezos at Amazon and Eric Schmidt at Google.

Ann’s career has given her a front row seat to some of the most significant technology shifts of the last two decades, from Amazon Prime and AWS to Android, DeepMind and Gemini. Her talk, “From Hype to Reality: AI That Drives Business Outcomes,” was delivered to Astorg’s portfolio companies and their CEOs.

While the subject was AI, the message was much bigger than technology.

It was about how businesses create value in moments of disruption.

Right now, access to AI is not the differentiator. Everyone has access to similar tools, models and platforms. The companies that will win are the ones with the leadership structures, decision making frameworks and operational courage to turn AI from experimentation into measurable value creation.

That distinction feels especially important for private equity backed businesses. In a PE environment, AI cannot remain an innovation theatre exercise. It has to support growth, margin improvement, operational leverage, customer experience, product innovation or enterprise value.

In other words, it has to move from hype into the value of the company.

AI advantage is not about access. It is about context.

One of Ann’s strongest points was that companies can have access to exactly the same technology and achieve radically different outcomes.

She called this the asymmetry principle: the idea that two organisations can start with the same technological opportunity, but only one turns it into a lasting advantage.

Her examples from Amazon made this tangible. Prime, Marketplace and AWS were not obvious bets at the time. They carried real cost, risk and uncertainty. But Amazon had built a decision making culture that allowed those ideas to be debated, protected and developed long enough to become transformational.

That culture included six page memos, rigorous analysis, intellectual challenge and single threaded leadership.

That is the lesson for AI. The technology matters, but the context around the technology matters more.

• Do senior leaders have the right framework to make decisions?
• Are they creating space for deep thinking rather than shallow consensus?
• Are teams being encouraged to debate, test and learn?
• Is anyone clearly accountable for moving a transformational idea forward?

Without that structure, AI becomes a collection of pilots. With it, AI becomes a value creation engine.

The golden ratio: where is your transformational 10 percent?

One of the most interesting ideas Ann shared was the golden ratio of innovation investment.

The model is simple:

• 70 percent core The products, services and operations that already work.
• 20 percent adjacent Improvements or extensions close to the current business.
• 10 percent transformational Bets that are new to the market, new to the business and potentially disruptive.

The point that stayed with us was not just that businesses should spend 10 percent on transformational development. It was that this 10 percent is often where future growth is created.

Most businesses are comfortable investing in the core. Many will invest in adjacent innovation. But transformational development is harder. It can feel distracting, risky or too far from today’s revenue model. In some cases, it may even cannibalise existing success.

But that is precisely why it matters.

Ann used examples like Kodak, Nokia and Blockbuster to show what happens when businesses protect the current model for too long. Each made decisions that were rational in the short term, but damaging in the long term. They optimised for what was already working and missed the market shift happening around them.

For CEOs and investors, the challenge is clear:

What is your transformational 10 percent?

Not your AI experiment.

Not your efficiency tool.

Not your incremental product improvement.

Your transformational 10 percent is the thing that could change your market position, redefine your offer, open a new revenue stream or create an advantage competitors cannot easily copy.

That is where AI becomes genuinely interesting.

From AI activity to value creation

A lot of organisations are currently asking: “How do we use AI?”

Ann’s talk pushed towards a better question:

“How does AI create value in this business?”

For PE backed companies, that framing is critical. AI needs to ladder up to the value creation plan. It should be connected to the commercial and operational levers that matter most:

• Customer experience.
• Sales productivity.
• Operational efficiency.
• Scalable delivery.
• Product innovation.
• Better data and insight.
• Stronger marketing performance.
• Increased enterprise value.

Ann referenced Klarna as a modern example of a company moving quickly from AI possibility to operational impact. The point was not just that Klarna used AI. It was that they acted faster, learned faster and embedded the technology into a business outcome while competitors were still forming committees and producing reports.

That speed matters.

Not reckless speed, but creative agility: the ability to experiment quickly, gather data, learn what works and become less wrong faster than the competition.

In emerging markets, no one has the perfect answer at the start. The winners are often the companies that shorten the learning loop.

Creative agility: getting less wrong, faster

One phrase from the talk really resonated:

How quickly can we become less wrong?

That is a useful way to think about AI adoption.

In established parts of the business, leaders often know the formula. They understand the inputs, the process and the likely outputs. But transformational AI opportunities are different. The formula is still being discovered.

That means leadership needs to create conditions for fast, intelligent experimentation. Not endless brainstorming. Not uncontrolled AI usage. But structured learning loops that help the business test assumptions, gather evidence and move with confidence.

This is where Ann’s framework around collective genius becomes practical. She described four elements that enable businesses to innovate repeatedly:

• Community of purpose A shared understanding of why the work matters and what the business is trying to change or create.
• Creative abrasion The willingness to debate ideas properly, challenge assumptions and avoid closing down disagreement too early.
• Creative agility Rapid experimentation, fast learning and data gathering.
• Creative resolution The leadership judgement to choose a path forward and commit.

For AI, this is a powerful model. It moves the conversation away from “which tools should we buy?” and towards “how do we build the capability to identify, test and scale what creates value?”

The Amazon lesson: better decisions need better structures

Another takeaway was the importance of decision making frameworks.

Ann talked about Amazon’s famous six page memo culture, where teams are expected to do deep analytical thinking before entering the room. Meetings are not built around presentations designed to persuade. They are built around reading, thinking, questioning and debating.

That matters because AI decisions are often complex. They cut across technology, operations, people, risk, data, customer experience and commercial strategy. A lightweight decision making process will often produce lightweight outcomes.

The question for leadership teams is:

Are we giving our senior people the right framework to make high quality decisions about AI?

Without that framework, organisations often fall into one of two traps.

They either move too slowly, waiting for certainty that will never arrive. Or they move too loosely, launching disconnected pilots that never translate into business value.

The better route is structured ambition: clear ownership, rigorous thinking, fast experimentation and a willingness to back transformational ideas.

The real AI moat is leadership

Perhaps the most important message from Ann’s talk was that the AI moat is not just technical.

It is leadership.

The businesses that make the biggest leap will not necessarily be the ones with the most tools. They will be the ones with leaders who can create the right context around those tools.

• Leaders who can protect transformational bets.
• Leaders who can create a culture of debate without paralysis.
• Leaders who can move fast without losing rigour.
• Leaders who can connect AI activity directly to value creation.
• Leaders who know when to stop optimising the present and start building the future.

For portfolio companies and CEOs, that is the challenge now. AI is no longer a future trend. It is a live test of leadership, operating model and ambition.

The opportunity is not simply to “do AI”. It is to use AI to make the business more valuable.

• To create better products.
• To serve customers faster.
• To unlock new efficiencies.
• To build new propositions.
• To develop the transformational 10 percent that could define the next phase of growth.

That is how we move from hype to reality.

And that is where the value is created.

How Show + Tell helps turn ambition into value

For us, Ann’s talk reinforced something we are seeing every day with the PE and VC firms we work with, and with the portfolio companies they support.

The opportunity is not simply to use AI. The opportunity is to use brand, digital, AI and marketing as practical levers for value creation.

That means asking better questions.

• Where can a stronger brand create more trust, differentiation and commercial momentum?
• Where can a better digital platform improve conversion, customer experience or operational efficiency?
• Where can AI remove friction, speed up delivery, improve decision making or unlock new services?
• Where can marketing become more measurable, more connected and more directly aligned to growth?

At Show + Tell, we work with PE and VC firms, as well as their portfolio companies, to answer those questions in a commercially grounded way. Our role is to help leadership teams identify where brand, digital, AI and marketing can create measurable value, then turn that thinking into clear strategy, practical delivery and momentum.

That might mean helping a portfolio company reposition for its next stage of growth. It might mean building a digital platform that supports acquisition, integration or international expansion. It might mean developing AI enabled tools, workflows or customer experiences that improve speed, quality or scalability. Or it might mean creating the marketing infrastructure needed to generate demand, improve visibility and support a stronger sales pipeline.

The golden ratio is a useful lens here. Most businesses already know how to invest in their core. Many are improving what sits adjacent to that core. The real challenge is identifying the transformational 10 percent: the ideas, platforms, propositions and operating models that could materially change the future value of the business.

That is where we believe the biggest opportunity sits.

AI will continue to dominate the conversation, but hype alone will not create enterprise value. Value will come from businesses that can connect emerging technology to customer need, brand strength, digital experience, operational efficiency and commercial outcomes.

That is the work we are excited about.

Helping ambitious businesses move from AI interest to AI impact.

Helping leadership teams turn digital ambition into practical advantage.

Helping PE and VC backed companies build the brand, platforms, products and marketing engines that support their next stage of growth.

Because the businesses that win will not be the ones that talk most about transformation.

They will be the ones that build it.