Tips to prepare technical executives for the era of generative AI

According to a report published Tuesday by Forrester Research, technical leaders looking to get the most out of generative AI for their organizations need to understand the basics of the technology.

“The tech world has been disappointed by several recent bubbles that show promise but deliver no real value, but generative AI is already improving content creation, software development, and knowledge management in enterprises,” notes the report.

“However, hype breeds misinformation and misunderstandings,” he continued. “Tech leads need to know some basics like what generative AI is, how it can be used, what the future holds for generative AI, and what to do with it in the near term.”

To understand what generative AI is, tech leaders need to dismiss some of the misconceptions about the technology.

“It sounds trite, but the biggest misconception I come across time and time again is that Generative AI and ChatGPT are not the same thing,” observed Rowan Curran, an analyst at Forrester and one of the report’s authors. .

“When leaders look at these things, it’s important to think of them as broad technology that just captured our imaginations through a chatbot interface,” he told TechNewsWorld.

“ChatGPT is an app wrapped around the GPT-4 or GPT 3.5 turbo model,” he said. “Tech executives need to look at models in addition to the application.”

Not as smart as it looks

Generative AI is a big language model, which means it’s very capable of anything language-related, explained Sagi Eliyahu, co-founder and CEO of Palo Alto, California-based manufacturer Tonkean. of a process experience platform that includes AI-enabled features. .

“Since we humans communicate and even think with words, LLMs now seem capable of anything,” he told TechNewsWorld.

“But even if they seem able to ‘think’, language models are ultimately limited by the data on which they were trained,” he said. “Like any technology, it’s only useful to the extent that you integrate it into the existing culture.”

“People think that because it sounds smart, it’s smart,” added Daniel Castro, director of the Center for Data Innovation, an international think tank studying the intersection of data, technology and public policy.

“People shouldn’t rely on it for facts or as a substitute for human expertise,” he told TechNewsWorld. “Instead, they should use it as a tool to generate ideas and increase people skills. Generative AI has many important use cases, but it’s still a far cry from general artificial intelligence.

Confusing generative AI with general artificial intelligence — a kind of AI that can perform any intellectual task a human can perform — is another misconception, argued Rob Enderle, the group’s president and principal analyst. Enderle, a consulting services firm in Bend, Ore.

“AGI is still years away from our future,” he told TechNewsWorld.

“What generative AI is is a big language model that can converse with you,” he said. “It’s the start of a new voice- and appearance-based user interface that, by design, is more human.”

Wide variety of use cases

The use of “chat” in a generative AI like ChatGPT can also confuse executives who are AI nimrods. “They confuse generative AI with simple chatbots commonly used for customer service on websites,” observed Mark N. Vena, president and principal analyst at SmartTech Research in San Jose, Calif.

“These chatbots are not generation AI-based, as they draw their answers from a finite universe of common questions that are usually topic-specific,” he told TechNewsWorld. “Gen AI organizes its materials, in theory, for all content on the internet, so it’s much more real-time from a relevant content standpoint and can answer a wide range of queries.”

While acknowledging that generative AI is still relatively immature, Forrester noted that tech leads can capitalize on a wide variety of use cases, including:

• Increase developer productivity with text-to-code generation tools;
• Enable visual designers to iterate and imagine quickly with text-to-image generators;
• Allow marketers to create product descriptions that match their preferred brand language and tone; And
• Increase executive presence by allowing synthetic avatars of themselves to appear in videos without having to register.

“One of the most underrated aspects of generative AI is its ability to empower more people to create software than has ever been possible,” observed Bob O’Donnell, Founder and Analyst. chief at Technalysis Research, a market research and technology consulting firm in Foster City. , California.

“No-code and low-code development tools have been available for years, but you still have to be very technical to make them work,” he told TechNewsWorld.

“One of the most exciting applications of generative AI is the ability to create code from descriptions,” he continued. “It means someone with an idea, without programming expertise, can do a lot of cool things. It’s going to have an incredible impact for businesses.”

From excitement to magic

Forrester noted that while generative AI is exciting today, tomorrow’s applications will seem like magic.

For example, a future analytics platform with built-in generative AI capabilities could allow a user to submit a query such as: “Create an infographic of revenue, operational expenses and customer satisfaction of the past year and include an explanation of trends summarizing our last three quarterly reports.

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“AI now allows end users to move from searching to something much more useful – solving,” Eliyahu said.

“And not just any kind of resolution, but differentiated, fast, personalized, context-aware resolution,” he continued. “At the end of the day, that’s what people really want and need from technology – for their tools to quickly understand and resolve their requests, questions and problems.”

Forrester admits problems have plagued generative AI. Text generators can produce consistent nonsense, as well as recreate harmful biases built into their data, he noted. Questions about copyright and intellectual property are also unanswered.

“Beyond the ability to hallucinate, which we’ve seen in a lot of these models, AI isn’t going to be a solution to everything,” said Will Duffield, policy analyst at the Cato Institute, a Washington think tank. , DC. .

“There’s always a risk of trying to over-engineer new technology to solve problems it’s not yet ready to solve,” he told TechNewsWorld.

Find the Gen AI vendor entry

Nonetheless, Forrester is encouraging technology leaders to experiment with generative AI over the next six to nine months.

“It’s really important for organizations to start experimenting in this space and start engaging with their vendor partners to understand what they’re doing,” Curran advised. “Most vendors have something on their roadmap for how they’re going to deliver generative AI capability.”

He also recommended that technical managers take a broad look at the vendor landscape. “It’s a lot bigger than some of the players who have gotten all the attention over the past few months,” he said.