Bridging the Gap Between AI Potential and Real-World Performance

By Shawn Hochstetler – VP of Business Solutions & Erin Crawford – Director, eTAi (eimagine Trust Advantage for Innovation)

Artificial Intelligence (AI) is rapidly transforming industries, promising unprecedented innovation and efficiency. The AI market size is projected to skyrocket to $1.8 trillion by 2030 – however many organizations are struggling and will struggle to realize AI’s full potential.

The Reality: Why Most AI Projects Fail

It’s a sobering fact: according to recent Gartner research, 70% of active AI projects will fail. The reasons are rarely technical; they are overwhelmingly human. For example:

• Only 21% of organizations report their team members have sufficient AI skills
• 73% of organizations lack the data maturity to effectively use data to drive decision-making
• 70% of broader transformations stall not due to technology concerns, but instead, because of organizational (people) issues.

AI isn’t just about machines and algorithms – it’s fundamentally about the people utilizing AI. Success hinges on trust, transparency, and comprehensive training. Without a plan for how your people will embrace, adapt to, and champion change, even the most sophisticated AI systems can and will fall flat.

That said, recent reports highlight that 67% of companies expect to increase their AI spend through 2027. If companies are going to continue increasing their spend, yet we know that more than half of AI projects are expected to fail, how do we ensure our projects succeed? That’s where Organizational Change Management (OCM) joins the conversation.

What Exactly Does Organizational Change Management (OCM) Mean?

Per Prosci, OCM is a structured approach that prepares, equips, and supports individuals and teams to adopt change and achieve desired business outcomes. With AI initiatives, this means building a bridge from potential to performance by ensuring that the team members associated with the technology change are ready and prepared to leverage the new business gains generated by the AI solution(s).

How Does OCM Drive AI Project Success?

Below are a few key ways a structured OCM enables an AI initiative to transition from projected business value into achieved business value.

1. Understand Project Goals:
   • OCM includes structured processes to wholistically assess changes and impacts from multiple angles – people, process, and technology perspectives.
2. Change Partner Support:
   • Formal OCM inclusion ensures we know exactly who is impacted and how. Impact assessments and mitigation planning are then conducted.
3. Tailored Change Management Plan Incorporated:
   • Project specific engagement and role-based training plans for affected groups are developed and executed, including clear metrics and success criteria to track progress.
4. Execute, Iterate, and Monitor:
   • OCM practitioners collaborate with project personnel (communications and training teams for example) to implement plans, monitor adoption, send surveys, and report results.

Along the way, continuous improvement occurs as feedback is received, adjustments made, and progress achieved.

OCM Is the AI Success Multiplier

AI is changing the business landscape rapidly, and organizations ready to change with it will benefit the most. OCM is the essential ingredient that turns AI investments into meaningful business outcomes – by focusing on people, fostering engagement, and delivering the training and support needed for success. If your organization is looking to harness the power of AI, make OCM a top priority.

Want to learn more? Our change practitioners at eimagine would love to engage with you. Contact us at sales@eimagine.com