- Generative AI is becoming a more common addition to employee workflows, according to an Insight Enterprises survey published last month in partnership with The Harris Poll.
- Nearly 3 in 4 workers use generative AI tools for data analysis and visualization, according to the survey of 601 leaders at companies with 1,000 or more employees. Two-thirds use AI-powered tools for research and email summarization.
- Other popular use cases include generating written content and crafting personalized learning. More than half are exploring generative AI in software development.
New Year's resolutions abound, and enterprise technology leaders are taking stock of what worked last year. They're also hoping to identify where moving from generative AI experimentation to implementation brings the most value.
It’s still early days for generative AI integration into enterprise workflows, but businesses are making inroads as strategies and deliverables come together, according to David McCurdy, chief enterprise architect and CTO at Insight Enterprises.
Across departments, leaders have been tasked with helping their company define the ROI of implementing generative AI. Potential advantages include improving customer satisfaction, reducing operational costs and boosting productivity, according to the report.
“Anytime you can put tools in the employees’ hands to solve problems and make them feel more productive, that allows you to have a competitive advantage and grow your business,” McCurdy said.
Though generative AI was doused in hype last year, analysts expect the frenzy will settle down. Gartner placed generative AI at the peak of inflated expectations in August with an impending drop to the trough of disillusionment on the horizon.
However, businesses are still ambitious about what the technology can do.
“We’re able to do things with the models that, frankly, have never been done, and beat AI that were trained over the last five to 10 years with four weeks' worth of tweaking and prompt engineering,” McCurdy said. “The time to value is the difference … and that’s why I think it’s here to stay.”
Leaders and employees alike are finding ways to make generative AI work better for them. This comes as reports of model behavior drifts push users to get creative and more specific with prompts, a strategy also deployed at Insight.
“We have one model where we’re actually reading contracts for legal teams, and so we tell it to … act like an advanced legal scholar that has worked in the industry for 20 years,” McCurdy said. “Telling the model what it should be good at helps it focus on finding the right information.”