Hype around ChatGPT, and the technology that powers it, has generated serious attention and reflection by finance leaders. The arrival of AI-generative technology has brought into question the value of human workers, and while its limitations are evident in industries like accounting and finance, the early evolution opens a tremendous amount of potential disrupting power.
While the uses of this new technology are still up for debate, leaders seem to agree on a timeline for incorporation. In a recent survey of just over 400 corporate leaders at the director level or higher, Insight Enterprises found nearly three-quarters (72%) of respondents want artificial intelligence incorporated into their business within three years.
Ethics, Use Case, and Regulation
Incorporation of new technology requires, among other things, a formulated approach and a communication strategy that lets employees feel like they are in the know and involved in the change. Not only is this technology unprecedented, it comes with a lore of job cutting, a phenomenon that can be an internal morale killer.
According to Insight Enterprise's data, leaders' opinions on the riskiest part about AI implementation diverge. Ethics, an area in which AI has already garnished in industries like music and education, is a concern for nearly a third (29%) of business leaders.
Customer service, a target of cost-cutting by leadership, is a prime candidate for the first types of AI integration. Customer support and service may be one of the first areas to incorporate generative chatbots into workflows, as two-thirds (66%) of leaders surveyed expressed interest in this area.
As the creators of the technology have instructed regulators to get involved in the progression of AI technology, no limits have been put in place yet. This approach is sensible, as regulators don't want to jump the gun on an emerging industry. Despite generate AI's impact on the conversations surrounding the future of work and the corporate landscape, AI is hardly an industry yet, with only a tiny market share of the technology space, few notable companies, and not a single IPO. While companies have begun calling themselves AI-powered, few incorporate it at a large scale outside of marketing.
Talent Retention and Happy Staff
Talent retention, one of the labor issues and challenges being felt by CFOs, shows no signs of becoming less of a problem anytime soon. Concerns around the employee reaction to widespread incorporation of ChatGPT and other generative AI tools is a significant factor in taking a measured adoption approach, data shows.
While some leaders may wish to subsidize employee work with AI, this involves major changes to how work is done and may be difficult to implement quickly. Nine in 10 (90%) respondents told surveyors they are concerned about AI replacing or reducing roles within their companies.
These factors, combined with the challenges in managing a multigenerational workforce, creates a complex environment to implement the technology.
Over a quarter (26%) of business leaders told surveyors their biggest worries were around workplace displacement, as good leaders know how important the people in their companies are to long-term success.
Making decisions that preserve the image of a company — whether in the eyes of fellow leaders, employees, customers, or investors — falls on the executive team. From cybersecurity woes to company decisions based on (corporate equality index) CEI indices, brand reputation has become paramount to leaders with goals to grow or develop new arms of the business.
Much like how a data breach destroys legitimacy in the eyes of both customers and investors, a sloppy incorporation of AI technology can yield similar results. Nearly a fifth (29%) of business leaders reported concerns about reputational risk in adopting AI technology.
AI integration runs the risk of frustrating employees, may negatively impact the customer experience, and can force changes in workflow that hurt productivity. Leaders must continue to evaluate the balance of AI benefits against these adoption risks while also being prepared for any bumps that may arise on the high-stakes highway of full-scale AI evolution.