Let’s say the quiet part out loud.
Implementing a revenue-generating, production-level AI solution is a bridge too far for many companies right now. More specifically, implementing Generative Artificial Intelligence (Gen AI) is something that extremely few enterprises are fully prepared to take on. Recent research published in Harvard Business Review and Forbes show nearly 80% of AI projects fail if you don’t have your data fundamentals under control. On the MIT Sloan podcast, “Me, Myself, and AI,” co-hosts Sam Ransbotham (Boston College) and Shervin Khodabandeh (BCG) focus on the fact that only 10% of companies succeed with AI.
With something this significant, why are failure rates so high?
For one thing, take a look at the portfolio of most C-level technology leaders. Across sectors, tech leaders are tasked with digital transformation which uproots the business model, recruiting within tight labor markets that create attract-retain staffing issues, engaging “return to work” vs “remote-first” policies that challenge networks and collaboration tools, supporting various modes of enterprise systems across cloud and on-premise infrastructure, launching data science products to gain customer insight, and keeping all of these attack surfaces secure from cyber threats. Shall we continue?
Digital and Technology leaders struggle to parse signals from noise.
Everywhere you turn someone’s going to be extolling the need for you to get your AI strategy and use cases lined up. A recent survey from Boston Consulting Group showed that 85% of executives are going to increase spending on AI and 89% consider Gen AI a “top 3 priority” for FY24. Software and service vendors alike want you to spend on AI. It’s not that you can’t start exploring. Effective leaders need to cut through the noise creating distractions and communicate a consistent vision that aligns people and outcomes.
Companies that are analytic competitors see the most gains as first movers on Gen AI use cases. They’ve made the investment in data management, statistics, and math for years and know what data serves as foundation for Gen AI success. There aren’t many ways to circumvent data when launching AI projects. If you don’t have this foundation set, your next step is clear.
Think of it another way: the AI/ML platform Hugging Face hosts over 350,000 ML models. Each model can contain hundreds of data inputs or outputs. We are moving away from data management and toward model management. If you do not have strong practices in place for strategic data assets, your AI initiatives will suffer or likely fail. Many companies are still placing people and practices around strategic information management.
So where do you start your AI roadmap? Set the tone.
Questions will abound. What is acceptable use? Are you looking to understand the implications of Gen AI in your market or are you wanting to enrich a competitive advantage of your firm? As a leader, what is the one thing you need to gain during this stage of the AI hype cycle? What is the near-term roadmap for Gen AI initiatives being considered? Who is accountable?
Cut through the hype and hyperbole to make meaningful progress. Articulate a compelling statement that clearly demonstrates why you’re making the investment, where you’re focusing on the business strategy, what you’re expecting as acceptable behaviors, and how you’re measuring the return. Setting the priorities, policies, and practices regarding the strategic direction of AI, provides signals for managing expectations of people both in and outside the company.
The era of AI is a battle for trust. Competing with Gen AI is not about chatbots and avatars. It’s about setting the edge where customers engage with your company in a digital ecosystem. Brand loyalty is tied to how customers perceive what your firm is doing with Gen AI. Employee attraction and retention ties-in to ethics in your hiring practices. If people distrust you they will disown you.
Get loud about what AI is and is not for your business goals. Clarify the strategic purpose of AI by creating a clear voice for the company, C-suite, and Board. Let your outcomes evolve with the market. Once you’re positioned to be heard, you’ll be ready to take on any AI challenge.
allen+cass consulting 