Upskilling ramps up as gen AI forces enterprises to transform

“Generative AI systems carry a lot of risk for enterprises,” he says. “There are risks around hallucinations, and the fact they’re black boxes in nature. And then there are the legal risks.”

Integrating gen AI in product, employee workflows

PhotoRoom is a 54-employee company that makes video editing software, downloaded by more than 100 million people, but it has two main challenges related to generative AI. The first, says Eliot Andres, co-founder and CTO, is to add the latest AI features to the app itself to keep it competitive. The second is to enable everyone at the company to use generative AI tools in their own workflows.

As soon as Stable Diffusion, the first open-source diffusion model, came out in mid-2023, the company immediately pivoted.

“We stopped everything,” says Andres. “We said, ‘Stop what you’re doing. This is going to be a game-changer for photography. We need to learn how to use those tools and integrate them into our product. This is a big deal.’”

To jump-start the process, the company held a three-day hackathon to understand what the new diffusion models were capable of.

“Since then, every time there’s a new technology, we tell people to use the latest tools,” he says. “There are new diffusion models coming out, and we’re always encouraging employees to play with them.”

The company also has an internal channel where the latest research papers are shared. One popular source of information on latest developments is @_akhaliq on X (formerly Twitter).

For internal workflows, the challenge is slightly different. Here, instead of learning about the underlying technical aspects of creating generative AI models, employees have to learn how to use generative AI tools.

PhotoRoom doesn’t have a formal training program, he says. Instead, the company uses a teach-by-example approach, with employees who find useful new tools educating their peers using Slack and other channels. Andres’ advice? Give employees the freedom to experiment.

“If you limit your employees to a single tool approved by the company, you might be missing huge opportunities or something that’s transformational for your company,” he says. “Let them find the best tools for their job. If someone uncovers a tool that boosts their productivity, encourage them and try to spread the word to other employees.”

Leveling up for generative AI

Healthcare technology vendor athenahealth has over 6,500 employees, more than 1,200 of whom are engineers, and generative AI is core to the company’s product development roadmap — and to internal productivity improvements. And training is how the company will get there.

“We’ve offered a number of rounds of training, including third-party prompt engineering training, and workshops,” says Heather Lane, the company’s senior architect of data science. “There’s an enormous amount of training material out there, so we don’t have to develop it all in-house. We’ve also brought in external speakers who’ve talked about both the high-level state of generative AI and specific materials about how it may be reflected in the healthcare space, where they see the technological development going, where they see the risk.”

So far, more than 700 people have attended generative AI knowledge sessions, more than 1,200 hours of generative AI training have been consumed, and 300 developers have completed a generative AI bootcamp.

The problem, she says, is there’s too much material out there, and most of it isn’t useful. Filtering down to the part you care about is the challenge, as well as the pace of change. “It’s not like drinking from a firehose,” she adds. “It’s like standing under Niagara Falls and trying to take a sip. It’s absolutely insane.”

Marketing takes the lead on gen AI

IT services firm Ensono has over 3,400 employees, just 27 of whom are in marketing. But it’s the marketing department that’s been spearheading generative AI.

“It’s helping us do more with less,” says Jonathan Bumba, the company’s chief marketing officer. “Things that used to take several hours now take a few minutes; things that used to take several days now get done in a few hours; and things that we couldn’t do before at all we can now do in a reasonable amount of time.”

The company is using a wide variety of generative AI tools to create content and connect with customers, including ChatGPT, Dall-E, Midjourney, Adobe Firefly, and Salesloft among others.

“We started playing with it right away,” he says.

When the technology first started coming out, the team was mesmerized. “Then we were disillusioned pretty quickly,” he says. “We’re just not prompt engineers. I wanted my team to lean in and embrace this, but I could feel the frustration of not getting the output we were looking for.” He tried Coursera and LinkedIn courses, but they just weren’t specific enough, Bumba says.

Even vendor-provided courses were too general. “Without knowing our workflows and what we’re trying to do, none of it was terribly helpful,” he says.

His team struggled to figure things out on their own until the middle of this year. Then in September, Bumba brought in a boutique consulting firm, AI Technology Partners, to identify specific generative AI use cases, figure out the right tooling, and create customized training workshops for employees based on his team’s actual workflows.

“After the training workshop was over, we still put them on retainer so we can reach out to them with real-world projects,” he says. “They walk us through it and help us build prompts so we can continue to do this after they’re gone.”

Looking back, he says he wishes he’d gotten help sooner.

“I waited too long to ask for help, wasting months thinking we could figure this out ourselves,” he says. “I’d like to have those months back. In this new world, a three-month delay means someone else had a three-month head start on me. In the world of AI, this matters. He or she who learns first, wins.”

Large-scale upskilling

“PricewaterhouseCoopers has the commitment to give its people the most in-demand skills for today and tomorrow,” says partner Robin Stein, who’s also the director of PwC Labs. “We realized very quickly we had to upskill our 75,000 people on the foundations of generative AI, how to apply gen AI responsibly, and how to become a prompt engineer.”

Because the company has a multi-generational workforce, it’s using a wide array of modalities, training approaches, and learning pathways, she says — everything from gamification to in-person seminars.

“Some people want to read an article and some want to listen to a podcast,” she says. “And there’s some gamification, including a live trivia game where people can earn rewards, which helps drive excitement about some of these programs.”

The final element is to give people tools they can use to apply these new skills.

“The adoption and engagement has been incredible, and people are highly interested and highly motivated to figure out how this will affect them,” she says.

Completing gen AI 101

Wipro Technologies is a technology and consulting firm with 245,000 employees. Of those, 200,000 have already completed basic generative AI training, says COO Amit Choudhary.

“We want all our people to be trained on generative AI,” he says.

The basic level of training includes a definition of what generative AI is, its history, and what responsible AI is all about.

“We want to educate our team members that there are risks to doing this,” he says. “And responsible AI means different things for legal people, for financial team members, or for cybersecurity experts.”

This program was developed in-house, he says, because the company started training earlier this year and there wasn’t enough external material available at the time.

Then employees move on to external training from external partners. That includes Udemy, Coursera, and LinkedIn, he says, as well as vendor-provided materials from companies like Microsoft, AWS, and Google for employees working on specific platforms.

Once the foundations are in place, Wipro offers industry- and function-specific training, such as what gen AI means for manufacturing, finance, HR, and supply chain management. As this is all created in-house, Wipro created an AI council earlier this year to handle it, tasked with building advanced courses customized to the individual requirements of the company.

There are hundreds of people involved in the training development process, Choudhary says, with a core team of over two dozen that creates the learning content and tracks its progress through the organization. Then there are all the people involved to execute the training plan, such as practice managers and service managers.

“We have consultants who are industry and domain-specific,” he says. “We have technologists who are high-end engineers, and a team of designers. We put all these people together, plus our partners and vendors. Our AI council sees the content coming in from outside, and the content we develop inside.”

And it’s not enough just to get the theoretical knowledge, he says. “Just telling them what it means is the first step. We’re also doing hackathons, and are now working on gamification of the training we already have. We also have our own platform for coders, where we give them live projects to work on as competitions. Once they’ve done some advanced courses, this is a problem they can solve.”