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The 70% rule: Why your AI strategy is a people strategy

How to redesign AI strategies for a competitive advantage

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Discussions about AI tools on company earnings calls reached an all-time high last year, becoming a top five CEO topic, based on analysis by The CEO Radar (nearly 5,000 company earnings calls). It shows that leaders discussed AI largely in the context of innovation and growth.

In fact, AI, tech, innovation and growth all showed increased mentions among CEOs in Europe and globally.

While CEOs are laser-focused on AI in earnings calls, there’s a risk they (and we) misallocate focus. Tracking the latest AI model achievements and possibilities – whether agentic or generative or something else - grabs attention. And getting algorithms and tech stacks in place is important.

The ROI blueprint: turning AI and automation into business value

Why AI’s investment must materialize for the C-Suite

But unlocking value is found in redesigning business processes and empowering people. AI is less an IT project and more a new chapter in how we think about, empower, and allocate human capital.

Yet only 21% of executives reported that their strategies passed four or more of Mc Kinsey’s Ten Tests of Strategy – a 40% drop from a decade and a half earlier, according to Mc Kinsey. It's a worry in a business world with high investments and expectations about AI.

Great focus on culture is needed to encourage innovation and a strategy to drive it while a transformative vision of how AI can make work better every day is essential. Strategy needs to improve how a business serves and adds value to its customers.

AI can fix problems, but its greater value is in giving business a competitive advantage. And this is best done with people and partners who have the advice and experience needed.

A powerful framework presented in new research by Boston Consulting Group argues that about 10% of value from AI comes from the algorithms themselves, 20% from the technology required to implement them, and a significant 70% from rethinking the people component.

That’s a sobering breakdown of how strategically guided transformation can succeed. Creating a culture of innovation, training and learning resources, and change management have taken on new importance as businesses chase AI ROI.

That must include presenting AI as a board level priority for growth, not merely an IT project and bring in middle managers as a core execution lever. The same piece of research says 88% of managers role model AI use and actively incorporate it into decision-making and daily operations.

How to take AI from pilots to deliver real business value

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AI projects worldwide are failing in businesses because of this simple reason

Middle managers connect senior leadership, strategy and the frontline where value is created, tasks are intelligently automated, and work is made better every day.

This framework is not theoretical. Consider how a manufacturer in wood production with an 80-year track record put this into practice to generate over £500,000 in annual savings. Its leaders spotted a gap in the market for an enhanced offering to customers and leveraged AI to advance the opportunity.

Competitors were selling lots of scanners needed for visual inspection but didn’t push improvements or provide upgrade packages.

This insight was coupled with the manufacturer’s own experience of old technology and outdated ways of working which led to false positives, increased waste and labor hours spent on manual checks and deteriorated working environments as its frontline workers processed up to 20,000 items a day.

Human insight, customer focus, and the right culture harnessed with strategy were turned into an advantage. It combined the expertise of its directors and project managers with that of partners, collaborating with a global leader in machine vision and AI solutions and a local partner for hands-on testing and implementation.

Its operations are now intelligently automated using machine vision software with deep learning and 3D sensors. The system plugs into production lines for consistent, reliable results under harsh industrial environments, and the AI continuously learns so precision and yield improve over time.

Outcomes include an eightfold improvement in precision, reduced errors, six-figure cost savings, and the confidence to expand its business into new global markets.

The benefits also extend outside the factory and into the supply chain, with much clearer visibility into each supplier's yield and quality profile when sourcing from different providers. The manufacturer has improved inventory accuracy and allocation, and shipment and production schedules run with confidence.

The system also helps overcome one of the industry’s biggest challenges: a shortage of skilled workers. With the AI-powered system, new team members can simply annotate images. The model then learns to recognize characteristics consistently, without needing a more qualified operator.

The lessons above and the 70-20-10 rule are clear: strategy without execution is a hallucination. But in the age of AI, execution is not simply about algorithms, but a workplace culture that empowers its people.

The critical questions for leaders are “What is our AI strategy?” and “Who is leading our business process transformation?” Get that execution answer right, and AI moves from a line item on an earnings call to the core engine of competitive advantage.

This article was produced as part of Tech Radar Pro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of Tech Radar Pro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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