Members of corporate boards are getting nervous about artificial intelligence, along with the potential implications for their businesses, it is reported.
“Public company board members say the swift rise of AI in the workplace is an issue that is keeping them up at night,” wrote Emily Glazer in a recent Wall Street Journal article that explored growing executive fears around AI. “Some point to recent concerns around employees putting proprietary code into ChatGPT, companies using generative AI to incorrectly source content or worries about so-called hallucinations where generative AI produces false or inaccurate information.”
There’s no turning back, of course, meaning that business leaders need to balance the risks of AI with its potential benefits. It seems we’ve been just led to expect too much too soon.
“While the long-term promise of AI is still enormous, a combination of aggressive marketing by AI vendors and positive public opinion puts unreasonable expectations on a nascent technology,” Flavio Villanustre, global chief information security officer of LexisNexis Risk Solutions, told Forbes. “AI still has significant limitations, including environmental impacts of high power demand, unsatisfactory outcomes due to hallucinations in many areas and other issues typical in the evolution of early-stage technologies.”
Considering the enormous hype around AI, and particularly generative AI, in recent times, one can be forgiven for assuming it is a miracle formula for business growth. “Investors are eager for a return on investment, and some even expect AI to move mountains in most use cases,” said Diane Gutiw, Ph.D, vice president of analytics, AI and machine learning for CGI. “The reality is that AI is simply another tool, albeit a powerful one, capable of solving problems previously too complex and costly to complete, such as interrogating documents and images.”
The key is to use AI “when it makes sense,” Gutiw continued. “If a business problem requires automation, AI has a place and should be considered when reviewing solutions. Focusing AI on strategic problem solving is where organizations will find the ROI.”
Business leaders’ nervousness about AI arises from a “mismatch between the benefits businesses expect from AI adoption and what the technology can deliver today,” Villanustre said. Add to this “limitations in AI technology that can hamper business processes, and even expose organizations to significant risk.”
For example, the rise of “regulatory compliance in cases where AI is used to manage personal information” poses risks, he said. “If the law requires organizations to expunge records for consumers who have expressed their desire for privacy, this is not a trivial operation in current AI models. Expunging a single record may require training the model in its entirety, potentially requiring days or weeks and very significant cost.”
Increased evidence of return of investment — even with these complications — may help assuage executive fears. “The primary barrier to adopting AI is demonstrating its business value,” said Gutiw. “By focusing on the problem at hand, rather than the tempting notion of using AI in every use case, businesses can be sure their investment is well worth it.”
More deeply understanding the capabilities of AI, along with its shortcomings, is essential. “Businesses need to put forth the effort to understand AI and identify the appropriate AI models to use before adoption,” said Villanustre. “Like any tool, the adequate use of AI can deliver significant returns on investment, but the incorrect use has the potential of risk and loss.”
Governance also is needed to maintain alignment with business needs and needs, measure results, as well as assure guardrails. “Organizations are also achieving some of the biggest benefits by ensuring there is clear AI and data governance in place to maintain and scale the solutions,” Gutiw said. “Keeping AI focused on solving a specific problem with measurable outcomes makes measuring and monitoring its reliability, robustness, and relevance easy.”
Ultimately, the success of AI “should be based on whether the business problem was solved and what benefits AI brought to the table,” she added. “There should be a clear advantage to solving problems with AI, whether it be cost, time, or resources saved.”
