May 27, 2025
In the digital world,
“why” comes before “how” in AI
Does your company know your “why” for AI?
Recent data from an IDC survey have shown that:
- 70% of CIO’s reported a 90% failure rate for their custom-built GenAI app projects
- 66% reported a 90% failure rate with vendor-led proof-of-concepts
These statistics clearly document that when a company starts with “how” instead of “why”, they fail much more often than they succeed. Burley Kawasaki, Head of Product Marketing & Strategy at Creation said it best: “Don’t start with what AI can do. Start with what your business needs to do better.”
Too many companies’ GenAI & Agentic AI projects are driven by a fear of missing out (FOMO) and being left behind by their competitors who are adopting and deploying it in their markets. As I wrote in my January blog fire-aim-ready is not a winning strategy for AI.
Here are some questions to help you find your “why” for AI.
- What is the business problem we are trying to solve or the business opportunity we are trying to seize?
- What must AI deliver to achieve that outcome?
- What resources do we need to successfully adopt & scale GenAI & Agentic AI?
- Do we fully understand the costs to move GenAI & Agentic AI pilots into production?
- Do we have the necessary skills and capabilities to effectively manage AI projects?
- What metrics will we use to measure the desired ROI?
- Do we have an enterprise-wide AI and Data governance process in place?
Releasing trapped value from run-the-business legacy systems & processes
A key driver to finding your “why” for AI is to identify and release the trapped value within your legacy systems and processes. The goal of this process is to identify bottlenecks and roadblocks that directly impede the performance and growth of your company.
Step One – Discovery: This step starts with a discovery process to document what percent of your budget and resources are allocated to running the business you have vs. growing the business you want. Based on doing this discovery work with multiple companies across multiple industries, the normal allocation is 80% run vs. 20% grow. This allows you to ask the question, “what would the ROI impact be on the company if this equation was flipped to 40% run 60% grow?”
Step Two – Recovery: This step involves a set of discussions with a cross-functional team to identify and prioritize legacy systems and processes that can be modernized, consolidated, or eliminated. In the facilitated workshops I’ve done with clients, we have recovered 15-20% of their budgets and time allocated to running the business for which there was little or no value or ROI.
Step Three – Redeploying: This step involves a set of discussions to create and prioritize a digital technology investment roadmap and timetable utilizing the recovered budgets and resources. In the work I’ve done with clients we have used the Stairway to Heaven model shown below as a guide. The value of this framework is that it prevents companies from investing in new digital technologies like AI, GenAI, and Agentic AI before they have adapted their systems of record infrastructure and operating model to successfully integrate it.
In addition, if your GenAI & Agentic AI pilots are not aligned with and in support of removing bottlenecks and roadblocks then it is unlikely that they will be successfully adopted and utilized. One of the major barriers to AI adoption is from employees who are afraid that it will take away their jobs. As such, it is critical to clearly communicate that part of your “why” for AI is to keep humans in-the-loop.
One of the major benefits of this process is that it enables companies to fund their new digital technology investments like AI from existing budgets and current resources.
Step Four – Implementation: This step involves developing a strategic AI roadmap that prioritizes AI initiatives that can be implemented in 30-90 days. Each of the initiatives is designed to either improve employee productivity and operating efficiencies or expand revenue opportunities and increase ROI. The leadership challenge is finding the right balance between funding the businesses you have and making sufficient investments in next-generation digital technologies that will drive long term growth.
To help companies evaluate the benefits and tradeoffs of where they should focus their AI investments, I have used the 4 Zones model framework shown below that my brother Geoffrey Moore developed for his book Zone To Win. Each zone highlights specific examples of where companies can remove system & process roadblocks and tackle new business growth opportunities using AI. In all cases, the final decisions are in service to their mutually agreed upon “why” for their AI.
There is little debate about the potential disruptive and transformative power AI, GenAI, and Agentic AI will have on how employees do their jobs and how companies engage with their customers and other key stakeholders. For your company to successfully compete as a digital enterprise, you must adopt and deploy AI across your organization. That process needs to start with finding your “why” for AI.
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