When generative AI made its grand entrance into the business world at the end of 2022, the initial panic was that the new tech was going to displace many human jobs. But it didn’t. Then, once we realized we had no idea how to use it efficiently and responsibly, suddenly we were going to need to hire even more humans to manage the AI doing humans’ work. But we didn’t. Now we’re realizing that staffing numbers are fine, we just need to embrace the skills necessary to have a productive coexistence with AI. But we haven’t—yet.
In fact, new research from tech industry and workforce nonprofit CompTIA shows that this harmony between man and machine is among the biggest obstacles organizations face in expanding their use of AI. The firm’s new report, Building AI Strategy, also finds that increased technology infrastructure costs to enable greater use of AI, and concerns about cybersecurity and privacy are other top challenges companies are addressing.
Few companies plan to develop their own AI algorithms
The majority expect to invest in existing technology tools, such as customer relationship management, business productivity suites and HR systems that have AI embedded to provide new features. These tools are already integral parts of corporate workflow. AI will become a powerful new part of a complex technology solution stack.
“Finding the best balance between their employees and new AI tools is front and center for many companies,” said Seth Robinson, vice president of industry research at CompTIA, in a news release. “There seems to be genuine interest in making their workforce more efficient through strategic AI applications and targeted upskilling.”
Skill-building requirements will be closely linked to an organization’s business plans and AI implementation approaches
The majority of businesses surveyed expect to invest in existing technology tools—such as customer relationship management, business productivity suites and HR systems—that have AI embedded to provide new features.
“These tools are already integral parts of corporate workflow, and AI will become a powerful new part of a complex solution stack,” Robinson explained. “In this scenario, a company will likely require a low degree of AI expertise across its entire workforce and a high degree of AI expertise in a few select areas.”
New AI framework highlights top skill-building concerns
The researchers have created an AI framework that identifies six areas where skill-building will be more important as AI is adopted throughout the technology stack.
- Cybersecurity professionals will be augmented with AI/ML capabilities to effectively secure their networks.
- Auto coding, where human engagement with AI/ML coding programs will grow.
- Architects will construct the networks where AI and ML live.
- Tech-adjacent staff working with AI will likely need to understand industry specific best practices for prompting AI/ML.
- The data analytics field will continue to evolve alongside AI/ML.
- System operations (SysOps), in business process automation, robotic process automation and other areas, will be enhanced by AI/ML.
Challenges related to the cost of AI implementation will also be affected by the implementation strategy a company follows. In the survey, 45 percent of firms cited the cost of infrastructure to enable AI as a challenge.
“Using cloud solutions or embedded functionality allows them to enjoy AI benefits without developing proprietary systems, thus reducing the likelihood of significant financial outlays,” Robinson said.
Cybersecurity and privacy concerns are also pressing, with 45 percent of companies ranking it high on the list of challenges. This may be an indicator of lessons learned when many firms leapt into new technology architectures or applications without fully considering the cybersecurity implications.
Download the full report here.
CompTIA surveyed 521 technology industry professionals on their insights and views on AI in initial stages of adoption.
