generative AI

Companies adopting artificial intelligence should avoid high-profile initiatives aimed at revolutionizing their businesses in favor of smaller projects with the potential to transform the organization incrementally by unlocking efficiencies and eliminating costs.

The emergence of ChatGPT last year propelled generative AI into the global spotlight. ChatGPT shattered records by attracting its first million users in five days and then soaring to more than 100 million users in just two months.  Since then, companies around the world have rushed to integrate generative AI into their operations, brands—and stock prices. As they do so, it’s easy for senior management to get caught up in the buzz and steer resources and attention toward the creation of game-changing new use cases.

Many of these announced projects will never see the light of day. According to research firm Gartner, nearly half of AI projects never get past the pilot phase. Among those that do make it into production, many fall short of expectations or fail to create any real value for companies and their customers.

Unfortunately, I fear those success rates could sink further with the current spate of AI investments. Companies are stockpiling AI talent. Although these new hires are brilliant and capable of whipping up algorithms in a flash, many lack real business experience and few have any deep expertise in complex businesses like banking or wealth management. As a result, these individuals are in a poor position to understand how to use their skills to create real value for the business. On the opposite side, most business leaders lack the technology knowledge and time needed to figure out how this cutting-edge technology can best be applied.

In all the excitement, it’s easy to overlook such cultural issues. But these disconnects between AI-driven innovation and actual business needs can undermine development projects and increase the risk of failure. For that reason, I believe senior executives working to integrate generative AI should focus less on the latest “cool tech” and more on their own organizations, workflows and corporate cultures.

The AI Academy

Rather than racing to introduce generative AI, senior management should first create internal structures that ensure alignment between the technology and the business. A great starting point is education. Given the importance of AI and other technologies to business today, companies should be rolling out programs that ensure their employees are up to speed and that their organizations are positioned to optimize growing technology budgets. For large companies, this could take the form of a full “AI Academy” that educates business leaders, line workers, senior management and even technology practitioners about the basics of the technology and how AI can be applied to business functions. Smaller companies can leverage Massive Open Online Courses (MOOC) and other online resources to educate teams.

Building Value, Incrementally

At the same time, companies should be identifying individuals within the organization that already have the right blend of technical expertise and business experience to create a long-term AI strategy. For example, at Broadridge, we brought together a small team devoted to identifying the highest-potential opportunities. One of the team’s most important conclusions was that, when it came to adding value to the business, the biggest opportunities came from the application of both traditional AI solutions and generative AI to core business functions. That finding helped senior management direct its focus away from flashy new development initiatives and toward a series of smaller projects that drove operational improvement.

That incremental approach allowed Broadridge to identify a host of opportunities to automate processes and otherwise enhance operational efficiencies. But the benefits did not end there. The same bottom-up process uncovered ways Broadridge could use generative AI to help its clients address inefficiencies in corporate bond trading. The result was the 2023 launch of BondGPT, an application powered by OpenAI GPT-4 that helps clients enhance liquidity and price discovery in the corporate bond market.

Collaborate, Experiment and Innovate

Finally, companies should be working to create an open source set of tools that allows teams to collaborate, experiment and innovate on new AI solutions. The latest versions of generative AI can be applied to a much broader range of functions than previous generations of the technology. This new wave of AI has applications in customer service, operations, product development and nearly all other business functions. The ability of generative AI to accelerate or, in some cases, even automate code generation creates opportunities for companies to create efficiencies virtually anywhere. Along those same lines, by democratizing the technology and making it so easy to use and apply, generative AI enables teams to rapidly develop new, high-impact use cases at scale throughout the organization.

The best way to foster that type of innovation is to avoid the temptation of “moon-shot” projects that promise to revolutionize the business overnight, and instead focus on a bottom-up strategy that uses both generative AI and more traditional AI tools to create a more efficient and dynamic business.

Generative AI allows a very rapid iterative development approach to validate the value very quickly.  We are seeing that GenAI projects can be delivered in weeks versus months.  In just six weeks we were able to conceive and deliver the first version of our BondGPT product which delivers pre-trade analytics for bond traders.