The AI strategist needs to understand how a company works at the corporate level, and coordinates with the executive team and external stakeholders to ensure the company has the right infrastructure and talent in place to produce a successful outcome for its AI initiatives. To succeed, an AI strategist must have a deep understanding of their business domain and the basics of ML. They must also know how AI can be used to solve business problems, says Dan Diasio, global AI leader at EY Consulting.
"Technology was the hard part years ago, but it's now reimagining how we wire our business to take the best advantage of that AI capability or AI asset that we create," he says, adding that an AI strategist can help a company think transformationally about how it uses AI. "To change the way [a company makes] decisions requires somebody with a significant amount of influence and vision to be able to drive that forward."
AI strategists can also help organizations obtain the data they need to fuel AI effectively. "The data that companies have inside their systems today or inside their data warehouses really only represents a fraction of what they'll need to differentiate themselves when it comes to building AI capabilities," Diasio says. "A part of the strategist's role is to look to the horizon and see how more data can be captured and utilized without overstepping privacy considerations."
AI governance strategist
Gen AI's emergence has put it firmly in the regulatory cross-hairs. Previous generations of AI brought with them data privacy and cybersecurity risks, but gen AI has the potential to do so much harm that an AI "kill switch" bill made it all the way to the governor's desk in California before being vetoed, even as other bills, regulating such areas as deep fakes, have been signed into law. There are also laws in the works -- or already in effect -- in many other jurisdictions, including the European Union.
But it's not just new regulations that companies need to watch out for. Cases related to copyright issues are working their way through their courts, and Air Canada was found to be responsible for the erroneous recommendations of its AI chatbot. There are also issues of bias, fairness, and ethics -- issues which, if not properly addressed, could lead to bad publicity, a drop in employee morale and retention, and loss of market share. To address this, Insight's Gentry recommends that an AI governance strategist be given responsibility to ensure that AI systems are developed and deployed responsibly, and to create frameworks and policies to govern AI use so there's adequate compliance with regulations and ethical standards.