Businesses struggle to balance AI tools and employee skills
When it comes to AI, tech leaders at large enterprises struggle with security concerns, infrastructure investments, and determining how best to apply AI tools alongside human talent, according to research from CompTIA.
Artificial intelligence promises businesses greater revenue, productivity, and operational efficiencies, but according to recent research from CompTIA, business and technology leaders feel challenged to determine where AI best fits within their workforce, how to secure it, and how to fund the infrastructure needed to support AI.
CompTIA, the nonprofit association for the tech industry and workforce, surveyed 521 business and technology industry professionals on their insights and views on AI in the initial stages of adoption for its “Building AI Strategy” survey and report. The results show that while respondents see many potential applications of AI in several areas of the business, they still feel challenged by understanding the best way to balance AI technology with their human workforce.
According to CompTIA, business and technology industry professionals are applying AI in the following ways:
- Automation: 67%
- Data analysis: 63%
- Cybersecurity: 61%
- Chatbot: 57%
- Software development: 57%
- Content creation: 57%
- Financial modeling: 54%
The majority of respondents also indicated they would be purchasing business tools with AI features as well as investing in AI tools from vendors. Fewer respondents said they’ll be developing their own tools for internal use. Among IT staff, 71% said they would be buying business tools with AI features, while 67% of business staff said the same. Thirty-five percent of IT staff said they would purchase AI tools from vendors, while 32% of business staff said they would do the same. And 28% of IT staff reported they would be developing their own tools for internal use as opposed to 20% of IT staff. CompTIA reports “the dominant approach is AI integrated into solutions,” such as customer relationship management, business productivity suites, and HR systems.
“These tools are already integral parts of corporate workflow, and AI will become a powerful new part of a complex solution stack,” Robinson said. “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.”
When CompTIA asked respondents about the most common challenges they are facing with AI, large enterprises cited the following challenges:
- Cybersecurity/privacy concerns: cited by 53% of large enterprises
- Cost of infrastructure to enable AI: 51%
- Determining best AI/human interaction: 46%
- Building appropriate datasets: 42%
- Ability to properly evaluate AI output: 39%
- Ability to provide proper inputs to AI tools: 37%
- Identifying clear use cases: 24%
Considering the concerns around AI, CompTIA created an AI Framework that identifies six areas in which business and technology leaders should build skills while AI is adopted throughout the technology stack. The six areas are: cybersecurity, auto coding, network architecture, data analytics, systems operations, and tech-adjacent staffing. These areas will be augmented with AI and machine learning capabilities, and the workforce will have to evolve alongside their AI/ML counterparts, according to CompTIA. Cloud computing will also help offset concerns around capital investments needed to support AI apps, CompTIA says.
“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.
