According to a Dice.com survey, 36% of AI professionals say most AI projects they support exist primarily to show investors and boards that the company is doing something with AI. These show projects waste budget, demoralise staff and widen the gap behind competitors who implement AI seriously. The fix starts with leaders tying their own KPIs to real AI outcomes.
The Current State of AI Projects: A Reality Check
A recent survey by Dice.com revealed a startling statistic: 36% of AI professionals believe that the majority of AI projects they’ve been asked to support are “primarily used to show investors, board members, or outside stakeholders that the company is doing something with AI.” This finding underscores a significant problem in the corporate approach to AI adoption.
While approximately half of all AI projects are considered strategically important, many companies are still caught in the trap of superficial AI engagement. This begs the question: why are leaders hesitant to fully commit to AI implementation?
The Root Causes of “For Show” AI Projects
Several factors contribute to the prevalence of superficial AI initiatives:
- Risk Aversion: Many leaders are unwilling to take substantial risks, especially with emerging technologies.
- Lack of Understanding: There’s a widespread knowledge gap among executives regarding AI’s potential and practical applications.
- Time Constraints: Leaders often lack the time to invest in learning about AI technologies and their strategic implications.
- Misaligned Incentives: Key Performance Indicators (KPIs) for most leaders are not tied to AI implementation, reducing motivation for meaningful engagement.
The Consequences of Inaction
Maintaining a façade of AI involvement without genuine commitment comes at a significant cost:
- Wasted Resources: “For show” projects consume valuable time, budget, and human resources without delivering tangible benefits.
- Missed Opportunities: While companies dabble in superficial AI projects, competitors are making strides in meaningful implementation.
- Demoralised Workforce: Employees who are enthusiastic about AI’s potential become disillusioned when projects lack substance.
- Widening Competitive Gap: A great AI divide is emerging between companies that commit to real AI integration and those that don’t.
Becoming a True AI Leader
For those ready to transition from superficial engagement to strategic AI leadership, consider the following steps:
- Educate Yourself: Invest time in understanding AI’s potential impact on your industry and company.
- Develop an AI Strategy: Create a comprehensive plan that aligns AI initiatives with your business objectives.
- Set AI-Related KPIs: Establish measurable goals tied to AI implementation to drive meaningful progress.
- Foster a Culture of Innovation: Encourage experimentation and learning around AI technologies.
- Allocate Resources Wisely: Direct funds and talent towards projects with potential for significant impact.
- Seek Expert Guidance: Don’t hesitate to reach out to AI specialists or consultants for support and direction.
Conclusion: It’s Not Too Late to Lead
The AI revolution is still in its early stages, and there’s ample opportunity for leaders to make a significant impact. If you believe in the potential of AI to transform your organisation, now is the time to act. Surround yourself with knowledgeable, motivated individuals who share your vision.
Remember, true AI leadership isn’t about having all the answers, it’s about asking the right questions and being committed to finding solutions. Whether you’re well on your way or just starting your AI journey, the key is to move beyond “for show” projects and embrace strategic, impactful AI implementation.
Frequently asked questions
What is a “show” AI project?
It is an AI project that exists mainly to signal activity to investors, boards or outside stakeholders rather than to deliver real value. A Dice.com survey found 36% of AI professionals say most projects they support are of this kind, doing something with AI for appearances rather than outcomes.
Why do so many leaders settle for show projects instead of real AI implementation?
Four causes recur: risk aversion around emerging technology, a genuine knowledge gap about what AI can do, lack of time to learn its strategic implications, and misaligned incentives, because most leaders’ KPIs are not tied to AI implementation, so there is little motivation for meaningful engagement.
What does a show project actually cost a company?
More than wasted budget. It consumes time and talent without benefit, lets competitors pull ahead with serious implementation, demoralises employees who were enthusiastic about AI, and widens the competitive gap between companies that commit to real integration and those that do not.
How does a leader move from show projects to genuine AI leadership?
Start by educating yourself on AI’s impact on your industry, then build a strategy aligned to business objectives, set AI-related KPIs, foster a culture of experimentation, allocate resources to high-impact projects, and seek expert guidance. True AI leadership is less about having all the answers than about asking the right questions.
Thomas Anglero is a Strategic AI Advisor, keynote speaker and author of Intro to Artificial Intelligence. He has delivered over 450 keynotes across 30 countries for organisations including IBM, the WHO, the World Government Summit and the European Commission. He founded the IBM Watson AI Lab for Cancer at the Oslo Cancer Cluster and closed over $500 million in enterprise transformation deals as CTO and Chief Innovation Officer at Cognizant.