At a time when economic recovery is slow and every investment must be carefully considered, AI has become a source of hope for many organizations. However, the reality is that many still have not seen clear results from their AI investments.
- More than 80–95% of organizations report that their AI projects have yet to deliver clear ROI.
- Less than 30% of organizations are able to deploy AI effectively at an enterprise-wide level.
The problem isn’t AI—it’s the way organizations invest in it.
Most organizations don’t fail because they choose the wrong technology, but because they start in the wrong place.
Common challenges seen across many organizations include:
- Purchasing AI tools in silos
- Providing one-off training sessions
- Viewing AI as solely an IT responsibility
Reality Check: The Numbers Behind the Failure
- Over 50% of organizations state that AI challenges lie in workflows—not in the models.
- More than 40% of AI budgets are spent on tools that employees do not use consistently.
- Organizations that cannot measure AI outcomes often stop further investment within 12–18 months.
Reframing the Mindset: Effective AI Must Start with the Work
AI that delivers real impact doesn’t begin with “tools,” but with the work that needs to be done better.
Organizations must shift their perspective.
- AI Tool > AI as Enterprise Infrastructure
- Individual Skill > Team Learning
- Experiment > Mini Flow Can using
Before the next AI investment, what should organizations ask?
- Who does our AI actually help work better?
- Are there workflows that people use consistently?
- How clearly can we measure the business outcomes?
MFEC Inspire 2026 – Empowering Tomorrow’s Enterprise with AI
A convergence of cutting-edge IT solutions, real-world use cases, and proven business outcomes.
This stage is not just about sparking ideas—it helps organizations establish the right investment foundation and move forward confidently in an increasingly challenging world.
