Enterprise AI Adoption
According to Gabriel Millien on LinkedIn, 83% of AI projects fail. This rate is more dismal than the Agile transformation success rates we used to see, that hovered around a 60% failure rate.
Millien wrote of six ways AI projects fail, calling these the expensive reality:
Legacy systems need full rewiring, about 6–12 months minimum.
67% of company data is “unusable garbage” and the cost to clean it up is > initial AI investment.
Shadow AI creates security nightmares. Every rogue AI instance is a new security vulnerability.
API costs spiral 3x over budget (at scale, $100k a month plus those lovely hidden fees)
Staff resistance kills implementation. Same problem, different transformation.
Compliance gaps are legal risks. Audit trails and ever-evolving privacy laws, for starters.
Let’s keep it affirmative. There is a way to change your organization with intention, but it does require focus and alignment. Sound familiar? You’re right. Most big changes or even true transformations need clear intent and supporting rigor to make incremental, lasting change.
Successful organizations aim to be ready before they go technical. Given the realities outlined above, what does it mean to be ready? Technology consultant (devops, devsecops, Agile, ML, LLM explorer, etc) and coach Lynda Menge gave this advice.
Enablement work (prepare for change): Build governance before releasing. A tech coach are far more effective at this than your high paid slide-producing consultants. This enablement work makes a path for change, and is part of the preparation phase of your overall organization change plan, outlined in item 2 below.
Enablement work (prepare for change): Train your teams on actual use scenarios, not the features of the AI you bought. Your tech coaches will really add value here. My advice: you need an organization change plan that clearly defines the training, communication, and management alignment activities for adoption. The plan is the plan. Leading with the plan, also called follow through, is the really tough stuff. And, it is critical to the success of the enterprise adopting AI and transforming.
Lead change: Lift up AI champions in each area/department/domain. Your tech coach can grow and develop them. My advice: your management needs to be aligned for this work to be successful. Successfully leading change needs a strong foundation: a vision and connected strategy. Make the time to establish the foundation, and then make more time to inspect and adapt what you asked your managment teams to do.
Sustain Change: As part of the metrics for adoption, set 12 months-or-less targets that are realistic. Your tech coach leads this discussion with senior management, which will enable them to lead change. Then, your senior management, can use what they learned and prepared for to lead change. The pace of change and your metrics need to be sustainable. Remember the failure rate?
This is a short but solid list for you to use and reflect upon. It’s a start to being intentional about the change or transformation you desire. Remember the three parts of building your adoption: Prepare for change, lead change, sustain change.
Tired of high investment and low maturity? I can help turn your ship around.