Many wonder how AI-driven efficiencies will affect various roles as generative and agentic AI continues to reshape various technologies and business workflows. Smoothstack COO and CFO Boris Kuiper shared his advice and insights on training workforces for the future with Channel Insider.
AI assists a variety of tasks, but it’s not a wholesale replacement for human talent
Smoothstack offers enterprises and federal agencies a variety of tech-driven talent staffing solutions to address ongoing shortages and demand for skilled workforces.
To Kuiper, even as AI proves valuable for various efficiency and productivity reasons, it is not an equal replacement for employees and the expertise they bring to an organization.
“AI is not as smart as we first thought it was,” Kuiper said. “There are limitations, and people can also struggle with how to best utilize it. Prompt engineering takes time to learn how to do properly, and there are still gaps in capabilities in these tools.”
Kuiper says AI tools are both an opportunity for developers to do their work faster and a reminder that humans are still required to keep companies running.
“At this point, you really have to be both. You need to know how to code really well on your own, and you need to be able to leverage AI to increase your efficiency and proficiency,” Kuiper said.
AI can still hallucinate in its answers, giving false information or, in the case of developers, faulty code. Kuiper says the best way to avoid errors or costly mistakes is to still have skilled workers who can check the validity of generated responses and use AI as a tool, not a replacement, to build needs faster.
“What we’re starting to call ‘AI-native developers’ are really the next generation of talent, and those people will have learned all the foundational aspects of development without relying on AI at first, and then they will also know how to use the AI to make that work better,” Kuiper said. “But right now, highly-skilled developers are often disincentivized to learn AI tools because they would take a productivity hit in the short term while learning, so we aren’t seeing adoption amongst those who are really skilled in the dev work right now.”
How organizations of all sizes can enable AI upskilling in their workforces
As much as the industry seems to talk about AI adoption, the data shows that many organizations have yet to bring AI into their workplaces at scale. For Kuiper, this points to a lack of strategic planning around how to integrate emerging technologies into a company’s everyday success.
“I still really only hear about Big Tech doing this, in terms of true adoption, and that’s for a few reasons, but especially difficulties with identifying the right use cases,” Kuiper said. “If you don’t know the use case, you can’t really use the tool.”
To drive AI adoption (and its associated benefits), Kuiper recommends that all organizations assign a leader to build an AI implementation strategy. Not every business can appoint a Chief AI Officer or a similarly titled role. Still, all organizations can assign someone (or a team) to set the appropriate guidelines and guardrails for their peers.
Additionally, Kuiper says, enterprises need to allow their employees the necessary time to truly learn how to utilize AI tools. This will likely come with a short-term decrease in productivity as individuals use their time to experiment with AI, but Kuiper says the long-term benefits of that far exceed any short-term drops.
“Organizations need to say, ‘we are going to invest in this learning curve because we know once you complete this, you will be better at your job,’ and then create the environment for that to be true,” Kuiper said.
Upskilling workers can take time and money, but those investments might pay for themselves quickly, given the race to stay ahead of competitors in AI adoption.
Many organizations continue to prioritize AI readiness. Read how Sherweb is helping channel partners enable customers to succeed with AI through a new program.