Telecom & Technology Consulting
Among their key responsibilities, CEOs must assure that their organizations keep up with the latest technical innovations. Falling behind, or being too slow to implement the new solution, can put them in a competitive hole that’s difficult to climb out of.
This is why CEOs often want to make technology transitions as soon as possible – seemingly starting tomorrow. But for CIOs, the challenge is bringing the company leader down to earth and distinguishing for them the hype from reality. Artificial Intelligence is one such case.
Every company has some level of “legacy” technology, tried and true processes, and cultural issues that take significant time to phase out. CIOs must spell out how the past can’t be transformed into the present overnight. They must do so by praising the CEO for their ambition while providing an honest, realistic assessment of what it takes for those goals to manifest.
There are, for example, complex issues regarding the infrastructure, governance, and training, and a major time commitment to switch to an AI-centric mode. That’s not exactly what CEOs want to hear. As such, point out the small wins you can achieve fairly quickly. There are many repetitive tasks where AI can improve workflows that teams are familiar with.
CEOs cannot only get caught up in hype of AI in general, they may also constantly change their minds on which particular model to implement. They read a blog post, or hear from other executives about a new model that claims to be even better than the current one they’re in love with.
Be sure to explain the importance of not getting caught up in that game. The key for a lasting and successful AI strategy has little to do with the model you’re considering— it’s all about the quality, governance, and clarity of the data that goes into the model. When you invest in getting the highest quality data, and the proper structure that supports it, you will perform to maximum capacity, no matter which model you choose. Don’t worry about trends, and instead focus on what you’re actually building.
Another concept to explain to CEOs is the issue of permissions. With our current use of dashboards, users know precisely what data will appear on a given page, which allows for the pre-determined set up for who has permissions to access specific data. Yet with AI, the system can generate outputs that were not set up previously.
The question is, how do you determine who has permission to see an unanticipated result? This task takes considerable time, since before deploying, for example, a filing a request, you must first determine whether your existing permissions and access control frameworks can handle outputs that were never planned for. The work must happen before you scale, rather than after the fact.
As mentioned earlier, AI implementation brings with it the necessity to shift, or change, the culture of work at your organization. For mostly every organization, engineers and analysts typically write code to build reports and define new processes. But with AI the key skill is editing, which means auditing AI output, assessing what may be incorrect, and understanding where to not blindly accept answers. CEOs must be brought up to speed on this skill gap, since investments must be made to help editing become a core competency.
There are other key AI implementation issues for which CEOs need education. But overall, they must be aware that the race to get up to speed is an iterative process, not a quick swap for one technology over another. It requires thoughtful analysis and envisioning all the potential ramifications on operations.
CEOs will always want the shiny new toy tomorrow. More than ever, CIOs must slow down this demand by guiding leaders to the most prudent choices – choices that maximize AI adoption while allowing the culture to easily adapt to the new way of working.
