Intelligence Curve

Where AI is actually earning its keep

Published: July 2026

As researchers, we live for the moments when a signal bubbles up out of the noise. For the work we do, this could be when a technology turns out to be quietly reshaping how an entire discipline works.

That was at the heart of why we built our emerging tech rankings. We wanted a holistic view of where the AI landscape was shifting, but also the ability to examine what that view might be leaving out: the gaps between what one community is building and what another is studying or buzzing about, at the very same moment.

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Where AI is actually earning its keep

Four months after our inaugural emerging tech ranking, we look at what shifted and what surprised us...

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Cyber resilience scales on machines. It succeeds with people

Published: July 2026

For nearly a decade, a central thread in our research has been the relationship between humans and machines. Time and time again, we’ve seen the organizations that pull ahead are the ones that figure out how humans and machines make each other better.

In 2018, when our colleagues Paul Daugherty, Accenture’s former technology officer, and Jim Wilson, Accenture Research’s global managing director of IT research, published Human + Machine, many people worried that AI would replace human workers. We presented a different view. The real opportunity lay in reimagining how humans and machines could collaborate. Each would do what the other couldn’t. That argument has been central to our research ever since. (One of Jim’s latest projects is an emerging technologies ranking that we explored in a previous Intelligence Curve issue. It tracks how ideas move from research to real-world use before they surface in the market. Look out for the latest iteration of the rankings in our next edition.)

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Cyber resilience scales on machines. It succeeds with people

The organizations that prove most resilient are the ones that solve the human + machine equation....

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What happens when the checkout window goes away?

Published: July 2026

In a recent edition, we introduced the idea of agentic commerce and what it means when AI agents acting on behalf of consumers find, evaluate and choose brands. We explored how the agent layer is reshaping discovery and brand visibility and why connecting with a machine requires a form of trust that machines and humans earn in different ways.

This edition goes deeper into what happens at the moment of purchase and what it means for the loyalty businesses have spent years building.

A simple way to think about what’s changing is to consider how you pay for something today. When you shop online, you probably already know how you’re going to settle up. You add your items to the basket, head to checkout and select your card, Apple Pay or even points, press “place order,” et voila. One to three business days later you’ll receive your package.

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What happens when the checkout window goes away?

As AI agents take over more of customers’ purchase journey, the loyalty and trust that businesses spent years building will face a new kind of test...

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Organizations that earn trust in AI build it in from the start

Published: June 2026

Something interesting happens when you talk about AI to different audiences. I have been on stage twice this month—once in Europe, once in New York—and I spotted subtle differences. Not in the questions exactly, but in the mood. The anxieties were different. The appetite was different. What struck me, though, is that underneath all of it, people were asking the same thing: can we trust this?

Part of what makes that question so charged is what AI systems actually are. They speak in human language. They take actions that look like human decisions. They learn from how we use them.

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Organizations that earn trust in AI build it in from the start

Why governance is now a growth strategy, starting with the architecture behind the agents...

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The probability stack could redefine what's possible

Published: June 2026

In business, management guidelines are based around the idea that the right answer exists and the job of a leader is to find it. It’s a worldview the French philosopher René Descartes would have recognized: reason as the path to certainty, logic as the ultimate guide.

Our technology followed the same logic. The computers are viewed as “certainty machines.” They operate on fixed rules and deterministic outputs.

But there is a category of problems that this foundation was never built to handle. Not because the technology wasn’t good enough, but because, as in life, some problems don’t have a single right answer. They live in uncertainty. Demand that shifts without warning. Supply chains disrupted by events no model predicted. Drug molecules with thousands of possible configurations.

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The probability stack could redefine what's possible

Your competitive edge isn't just about having the right technology; it's also knowing which assumptions to test with that tech...

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Planning for multiple futures at once

Published: April 2026

There’s a tendency, in business and in life, to plan around what feels likely. The scenarios we outline and decisions we make are often built on patterns we’ve seen before. But the events that most profoundly influence our lives are often those we don’t fully prepare for, even when their consequences can be severe. In other terms it is critical to anticipate potential events with low probability and high impact.

Author Nassim Nicholas Taleb captured this idea in his book The Black Swan. He used the now famous example of a turkey that grows more confident in its safety with each passing day it’s fed and cared for. That is until it meets its Thanksgiving Day fate. His point was not just about unpredictability (from the bird’s point of view), but about how easily we rely on past experience to guide future decisions.

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Planning for multiple futures at once

Agentic AI is making real-time scenario planning accessible to any organization navigating uncertainty...

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What can emerging technologies tell us before they fully arrive?

Published: May 2026

Much of the conversation around emerging technology tends to focus on what’s most visible. The latest models, the newest applications, the breakthroughs that make headlines. These moments matter, but they’re often the result of changes that have been percolating for some time, out of view.

For those trying to understand where the curve is moving, the harder question isn’t just what’s happening now, but what signals are forming beneath the surface and how to interpret them before they become obvious.

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What can emerging technologies tell us before they fully arrive?

A new ranking tracks how ideas move from research to real-world use before they surface in the market...

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The AI skills reset

Published: April 2026

There’s a lot of discussion about how AI will change work, often focused at the level of jobs: What will be lost? What will be created? And while that conversation is important, it only captures part of what’s happening. What we’re seeing in the data is something more fundamental: The composition of work is changing.

I see this in the students I teach. They are quick to adopt AI and use it to expand what’s possible. At the same time, what matters most isn’t new. The ability to lead, exercise judgment and use creativity to solve problems remains central. If anything, these skills are becoming more important as AI becomes embedded in how work gets done.

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The AI skills reset..

By breaking work into its core components, leaders can develop a clearer, more precise view of where AI creates value and how to capture it.

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The probability stack could redefine what's possible

Published: May 2026

Digital commerce has delivered on many of its original promises. Shopping is faster, more convenient and available at any hour. And yet, anyone who’s tried to book a transatlantic flight with the family cat knows the experience can still unravel quickly. You find the right flight, but then you find the pet policy buried in an FAQ that’s different on every airline, with a cabin limit nobody advertises clearly. You call to confirm. You get transferred. You start over.

Given how far we’ve come, this complexity shouldn’t still exist.

That gap between what digital commerce promised and what it actually delivers is what makes the latest research from our team worth paying attention to. As one of my colleagues put it, digital commerce has largely been tolerated. It’s certainly not loved. Now, the architecture of commerce itself is being reconsidered.

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When agents do the shopping

What agentic commerce means for your business, from three different angles.

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What executives can learn from their digital twins

Published: March 2026

Last year, I wrote about what I called a “Big Bang” moment in research. For decades, the process of generating insight followed a familiar pattern: define the question, design the survey, collect responses, analyze the results. It worked well, but it moved at the pace of weeks and months.

What caught my attention then was the emergence of agent-based research—using synthetic agents to simulate how leaders, consumers or employees might respond to a question. Insights could be generated within days, at greater scale and far lower cost.

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What executives can learn from their digital twins

The most valuable insights sometimes appear when human judgment and machine logic disagree...

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The next edge belongs to those who scale intelligence

Published: March 2026

Welcome to the first edition of Intelligence Curve. I’m Francis Hintermann. I lead Accenture Research, a global team that studies how markets shift, how new technologies reshape performance and how leaders translate insight into action.

I’ve spent much of my career studying how technologies evolve—how they rise, reshape markets and enable organizations to innovate and reach a higher level of performance. The “curve” has always been central to that work: understanding where we are in an arc of change and what comes next.

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The next edge belongs to those who scale intelligence

As capital reshuffles in the Age of AI, who is positioned to capture value?

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The AI skills reset

Published: April 2026

There’s a lot of discussion about how AI will change work, often focused at the level of jobs: What will be lost? What will be created? And while that conversation is important, it only captures part of what’s happening. What we’re seeing in the data is something more fundamental: The composition of work is changing.

I see this in the students I teach. They are quick to adopt AI and use it to expand what’s possible. At the same time, what matters most isn’t new. The ability to lead, exercise judgment and use creativity to solve problems remains central. If anything, these skills are becoming more important as AI becomes embedded in how work gets done.

Read full report

The AI skills reset..

By breaking work into its core components, leaders can develop a clearer, more precise view of where AI creates value and how to capture it.

Read Report

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