by Robyn Bolton | Aug 20, 2025 | AI, Metrics
Sometimes, you see a headline and just have to shake your head. Sometimes, you see a bunch of headlines and need to scream into a pillow. This week’s headlines on AI ROI were the latter:
- Companies are Pouring Billions Into A.I. It Has Yet to Pay Off – NYT
- MIT report: 95% of generative AI pilots at companies are failing – Forbes
- Nearly 8 in 10 companies report using gen AI – yet just as many report no significant bottom-line impact – McKinsey
AI has slipped into what Gartner calls the Trough of Disillusionment. But, for people working on pilots, it might as well be the Pit of Despair because executives are beginning to declare AI a fad and deny ever having fallen victim to its siren song.
Because they’re listening to the NYT, Forbes, and McKinsey.
And they’re wrong.
ROI Reality Check
In 20205, private investment in generative AI is expected to increase 94% to an estimated $62 billion. When you’re throwing that kind of money around, it’s natural to expect ROI ASAP.
But is it realistic?
Let’s assume Gen AI “started” (became sufficiently available to set buyer expectations and warrant allocating resources to) in late 2022/early 2023. That means that we’re expecting ROI within 2 years.
That’s not realistic. It’s delusional.
ERP systems “started” in the early 1990s, yet providers like SAP still recommend five-year ROI timeframes. Cloud Computing“started” in the early 2000s, and yet, in 2025, “48% of CEOs lack confidence in their ability to measure cloud ROI.” CRM systems’ claims of 1-3 years to ROI must be considered in the context of their 50-70% implementation failure rate.
That’s not to say we shouldn’t expect rapid results. We just need to set realistic expectations around results and timing.
Measure ROI by Speed and Magnitude of Learning
In the early days of any new technology or initiative, we don’t know what we don’t know. It takes time to experiment and learn our way to meaningful and sustainable financial ROI. And the learnings are coming fast and furious:
Trust, not tech, is your biggest challenge: MIT research across 9,000+ workers shows automation success depends more on whether your team feels valued and believes you’re invested in their growth than which AI platform you choose.
Workers who experience AI’s benefits first-hand are more likely to champion automation than those told, “trust us, you’ll love it.” Job satisfaction emerged as the second strongest indicator of technology acceptance, followed by feeling valued. If you don’t invest in earning your people’s trust, don’t invest in shiny new tech.
More users don’t lead to more impact: Companies assume that making AI available to everyone guarantees ROI. Yet of the 70% of Fortune 500 companies deploying Microsoft 365 Copilot and similar “horizontal” tools (enterprise-wide copilots and chatbots), none have seen any financial impact.
The opposite approach of deploying “vertical” function-specific tools doesn’t fare much better. In fact, less than 10% make it past the pilot stage, despite having higher potential for economic impact.
Better results require reinvention, not optimization: McKinsey found that call centers that gave agents access to passive AI tools for finding articles, summarizing tickets, and drafting emails resulted in only a 5-10% call time reduction. Centers using AI tools to automate tasks without agent initiation reduced call time by 20-40%.
Centers reinventing processes around AI agents? 60-90% reduction in call time, with 80% automatically resolved.
How to Climb Out of the Pit
Make no mistake, despite these learnings, we are in the pit of AI despair. 42% of companies are abandoning their AI initiatives. That’s up from 17% just a year ago.
But we can escape if we set the right expectations and measure ROI on learning speed and quality.
Because the real concern isn’t AI’s lack of ROI today. It’s whether you’re willing to invest in the learning process long enough to be successful tomorrow.
by Robyn Bolton | Jun 25, 2025 | Leadership, Stories & Examples, Strategy
Convinced that Strategic Foresight shows you a path through uncertainty? Great! Just don’t rush off, hire futurists, run some workshops, and start churning out glossy reports.
Activity is not achievement.
Learning from those who have achieved, however, is an excellent first activity. Following are the stories of two very different companies from different industries and eras that pursued Strategic Foresight differently yet succeeded because they tied foresight to the P&L.
Shell: From Laggard to Leader, One Decision at a Time
It’s hard to imagine Shell wasn’t always dominant, but back in the 1960s, it struggled to compete. Tired of being blindsided by competitors and external events, they sought an edge.
It took multiple attempts and more than 10 years to find it.
In 1959, Shell set up their Group Planning department, but its reliance on simple extrapolations of past trends to predict the future only perpetuated the status quo.
In 1965, Shell introduced the Unified Planning Machinery, a computerized forecasting tool to predict cash flow based on current results and forecasted changes in oil consumption. But this approach was abandoned because executives feared “that it would suppress discussion rather than encourage debate on differing perspectives.”
Then, in 1967, in a small 18th-floor office in London, a new approach to ongoing planning began. Unlike past attempts, the goal was not to predict the future. It was to “modify the mental model of decision-makers faced with an uncertain future.”
Within a few years, their success was obvious. Shell executives stopped treating scenarios as interesting intellectual exercises and started using them to stress-test actual capital allocation decisions.
This doesn’t mean they wholeheartedly embraced or even believed the scenarios. In fact, when scenarios suggested that oil prices could spike dramatically, most executives thought it was far-fetched. Yet Shell leadership used those scenarios to restructure their entire portfolio around different types of oil and to develop new capabilities.
The result? When the 1973 oil crisis hit and oil prices quadrupled from $2.90 to $11.65 per barrel, Shell was the only major oil company ready. While competitors scrambled and lost billions, Shell turned the crisis into “big profits.”
Disney: From Missed Growth Goals to Unprecedented Growth
In 2012, Walt Disney International’s (WDI) aggressive growth targets collided with a challenging global labor market, and traditional HR approaches weren’t cutting it.
Andy Bird, Chairman of Walt Disney International, emphasized the criticality of the situation when he said, “The actions we make today are going to make an impact 10 to 20 years down the road.”
So, faced with an unprecedented challenge, the team pursued an unprecedented solution: they built a Strategic Foresight capability.
WDI trained over 500 leaders across 45 countries, representing five percent of its workforce, in Strategic Foresight. More importantly, Disney integrated strategic foresight directly into their strategic planning and performance management processes, ensuring insights drove business decisions rather than gathering dust in reports.
For example, foresight teams identified that traditional media consumption was fracturing (remember, this was 2012) and that consumers wanted more control over when and how they consumed content. This insight directly shaped Disney+’s development.
The results speak volumes. While traditional media companies struggled with streaming disruption, Disney+ reached 100 million subscribers in just 16 months.
Two Paths. One Result.
Shell and Disney integrated Strategic Foresight differently – the former as a tool to make high-stakes individual decisions, the latter as an organizational capability to affect daily decisions and culture.
What they have in common is that they made tomorrow’s possibilities accountable to today’s decisions. They did this not by treating strategic foresight as prediction, but as preparation for competitive advantage.
Ready to turn these insights into action? Next week, we’ll dive into the tools in the Strategic Foresight toolbox and how you and your team can use them to develop strategic foresight that drives informed decisions.
