Why most AI projects are failing (and how yours can succeed)

The AI implementation paradox

McKinsey estimates AI could contribute $4.4 trillion annually to the global economy, while Goldman Sachs suggests AI advances could boost global GDP by 7% over the next decade. Yet despite this extraordinary potential, organisations worldwide face a sobering reality: more than 50% of generative AI projects are failing, with at least 30% likely to be abandoned after proof of concept by the end of 2025.

This isn't a technology problem—it's a preparation problem. Through extensive client work and cloud provider partnerships, we've found that the success of many AI project centres on foundational decisions made before implementation begins.

The key takeway: asking the right questions before deciding on the AI answer can lead to lasting success.

The six-question framework

That’s why we've identified six strategic questions that consistently predict AI success.

When organisations systematically address these questions before implementation, they achieve demonstrably superior outcomes. They turn AI investment into measurable competitive advantage rather than contributing to the statistics of abandoned POCs or costly pivots.

Each question addresses fundamental preparations required before any AI technology deployment. Rather than focusing on technical specifications or vendor selection, this framework ensures you build the strategic and operational foundations that determine long-term success.

Deliberately simple, you can think of these questions as an AI readiness checklist—one that can help makes sure your AI project moves beyond POC and becomes a competitive advantage for your business.

From preparation to competitive advantage

The evidence for systematic preparation is compelling. Our research demonstrates that organisations implementing within structured frameworks are twice as likely to see improved ROI on their digital initiatives. And we’ve seen multiple client engagements where proper preparation enables the kind of breakthrough results that justify an investment in AI.

These aren't isolated success stories. They're examples of what happens when organisations prepare systematically rather than rushing into implementation.

Consider Orange County United Way's approach to their 2-1-1 crisis response service. Rather than pursuing AI broadly, they established specific, measurable objectives: dramatically reduce wait times for people in crisis, improve service delivery efficiency, and scale support capacity without proportional cost increases.

This strategic clarity enabled targeted technology selection and sustained executive support. Working with us to deploy Amazon Connect's AI-powered contact centre solution, they achieved an 85% reduction in wait times—from 11 minutes down to under 2 minutes. That's not just an improvement—it's a complete game-changer for people in crisis situations.

We have a very lean team. We have a wealth of books and a wealth of ideas, but the creation of activities—meaningful activities that are specifically aligned with a book—that's a labour-intensive effort. We had been thinking, 'What are some ways we can use GenAI to be an extra hand in the factory here?

- Sonny Lacey, Director of Product, Worldreader

With SoftwareOne's guidance and the use of BigQuery, we removed obstacles that prevented our in-store and corporate teams from sharing information effectively. This has been a big success. We're now even better at setting sales goals and increasing in-store sales.

- Cristina Frontera Rossello, Business Technology Project Manager, Camper

With these successes in mind, consider using this six-question framework to assess your organisation's own readiness before implementing your next AI initiative:

Organisations that answer these questions create the conditions where AI delivers sustained competitive advantage.