While nearly every company has adopted digital transformation buzzwords in recent years, the actual implementation of these disruptive technologies remains another story. For a variety of reasons, new technologies often fail to meet expectations. One example is artificial intelligence, which is an advanced technology that companies cannot ignore in an era of increasing digitalization and remote work.
Many organizations deploying AI projects through tactical initiatives that seek to deliver an immediate payback have learned that this approach rarely delivers meaningful value. AI is a powerful tool, one that has the capacity to redefine entire industries. But delivering on that potential is hard and will not be achieved through piecemeal projects.
Organizations that limit their AI investments to incremental and opportunistic deployments without a broader strategic vision risk losing their competitive advantage to those that define a new vision for their enterprise and pursue that with purpose and drive. That's why visionary leaders are the key to unlocking the latent power of AI.
A common first step for an Organization embarking on its AI journey is to establish an AI Center of Excellence (CoE). The CoE harvests business cases from across an enterprise and identifies willing partners in the business. Typically, these AI projects are conceived and designed at the lower levels of an Organization and then pursued by talented (but junior) AI engineers. All too often, there is poor alignment between what a business wants and what its technical team can deliver. Well-designed projects close this gap iteratively as both the business and the AI team learn what is possible to achieve and what is truly needed to deliver value. Unfortunately, it's more likely that neither side has the experience, sophistication or sponsorship to bridge this gap. As a result, both sides depart frustrated. Even projects that deliver value for a given business often run aground when it comes time to scale. Scaling requires collaboration from multiple cross-functional teams: IT to provide the infrastructure, risk management, HR to provide training and senior business stakeholders to provide sign-off. Unfortunately, one-off projects with limited value struggle to obtain bandwidth and priority from these teams. Given these challenges, it's no surprise that many AI projects fail to deliver on their intended benefits. However, AI engineers at the ground level aren't to blame. The problem starts with a lack of vision from senior leadership. The effort to elevate the strategic focus of AI starts by engaging people who own big business problems. Then find goals that are sufficiently compelling for everyone to support the investment and pain of enacting them. This sets teams up for success and gives them the flexibility to adjust their goals as necessary.
