Bridging the AI Skills Gap: Training Your Workforce for Success

The push to integrate AI with business operations and deliver AI-based solutions to the public continues to increase dramatically. One recent study shows that companies adopting AI for at least one business function increased from 55% in 2023 to 78% in 2025. The pace of AI investment has not slowed either. But this investment often overlooks a critical area of AI implementation—training.

Companies implement AI faster than they can train employees on how to make the best use of it. This gap will only grow as organizations realize the benefits of successfully leveraging AI and more companies seek to capitalize on this powerful emerging technology without considering the outdated skillsets of the employees best positioned to make it work. According to Deloitte, 57% of businesses report that their workforce lacks the skills needed to adopt AI successfully. That represents significant room for improvement.

The Dual Challenge: AI Transformation + Deepening IT Skills Shortage

Most organizations find adopting AI a heavy lift. The hardware expense, infrastructure overhaul, and network augmentation required to deliver a promising ROI create significant demands for any company. Adding training time and cost on top of that may not appeal to decision-makers. But if a company wants to lower costs and realize all the benefits AI can offer, it should seriously consider a plan to get current employees up to speed. While this requires substantial effort, evaluating and remedying current skill gaps, along with identifying prospective operational boosts, should form part of any AI adoption plan.

Looking Within, not Without

While hiring an AI specialist to assist with a new AI solution certainly seems practical and appealing, this approach cannot solve the AI skills gap problem alone. For one thing, these experts remain in short supply. The newness of the technology, coupled with the pace of AI adoption, has created demand that well exceeds supply, meaning that AI experts are not only hard to find but can command top dollar for their services. Bain & Co. predicts that AI job demand could exceed 1.3 million jobs over the next 2 years, while supply currently tracks to fill less than 645,000 of those jobs.

This suggests that upskilling current employees rather than hiring top talent from outside the company offers a more practical approach. Companies should also consider the impact on morale of hiring externally rather than providing existing staff, who often hunger for opportunities, the chance to evolve in their respective jobs. From the outset, experts have touted AI as a means to augment the capabilities of human workers rather than replace them outright. Organizations need to carefully apply this mindset to current staffing models as well.

5 Roles Most Likely to be Impacted by AI

While companies can apply both agentic and generative AI across departments, specific areas of business are especially well-suited to benefit from this technology. Efforts to upskill current staff may need to focus on these areas:

Operations

Here organizations can leverage many of the automation possibilities that AI implementation offers. Many companies looking to leverage AI primarily focus on the capabilities to automate routine, repetitive tasks that don’t necessarily require extensive human input.

Marketing

If an organization collects enough useful data about its customers or potential customers, AI can analyze that data to deliver targeted marketing campaigns and identify opportunities for new business.

Customer Support

This area already exposes many people to some form of AI interaction. Companies can use the technology to quickly resolve customer issues more complex than the bots of the recent past could handle. It can also automate follow-ups and align with marketing directives to deliver more targeted correspondence.

IT

While AI cannot rebuild a server, it can help identify optimal configurations for IT infrastructure and continuously monitor systems to identify vulnerabilities and opportunities for improvement in efficiency. Engineers already leverage AI to create code, currently using it as a starting point for programming.

Analytics

This area showcases where AI can really impress, with its ability to compile and analyze massive amounts of data with lightning speed.

AI Skillsets, a Shortlist

Other divisions of a company will likely experience AI’s impact, so next, we will focus on specific skill sets, some of which may span operational areas. Below you’ll find a comprehensive, if not exhaustive, list of skills that effective AI upskilling can foster.

Basic AI Concepts

Organizations should address the most obvious gap quickly. Getting employees up to speed on the basics of AI, including what it is and, critically, what it isn’t, proves crucial to the success of an AI implementation.

Prompt Engineering

While engaging with AI requires slightly more complexity than a pre-AI Google search, the same principle still applies: asking the right question. Employees whose jobs now include collaborating with an AI application need to understand that better prompts will lead to better results.

Data Literacy

Organizations need to address two essential elements regarding data. First, they must curate the data they provide to an AI solution so that only the most useful and unbiased data influences conclusions. Second, staff must successfully interpret the insights that AI efforts generate to align with business needs.

Understanding Agent Workflows and Automation Triggers

Employees must grasp the dynamics of AI collaboration, understanding what events will trigger AI into action as well as how the adaptable path AI takes deviates from traditional, if-then workflows that follow much more rigid definitions.

No-Code Logic and System Thinking

AI can empower non-engineers to develop the aforementioned workflows using visual interfaces and pre-built components, while providing those available components through a powerful systems thinking approach that analyzes a collection of interdependent parts and helps staff create the most efficient flows.

Critical Thinking and Oversight in AI Decision Loops

Human involvement remains critical to AI’s success. Left to its own devices and with suspect data, an AI model could potentially arrive at incorrect conclusions. A Human-in-the-Loop approach, where human skills of judgment, interpretation, and empathy play integral roles, proves critical to the success of an AI-driven endeavor.

Mind the Gap

After a careful analysis of skill gaps, the next step involves developing an approach to close those gaps, and here are some of the more successful techniques to achieve this critical directive:

Internal Bootcamps

Depending on the extent to which AI integrates with operations, organizations may need a crash course in Artificial Intelligence. This proves especially true if significant gaps emerge in the current workforce’s basic understanding of what AI is during an evaluation.

Peer-Led “AI Champions” Programs

Like with any new technology, buy-in proves critical to the success of an implementation. If your staff doesn’t like or understand the new technology, the odds of them getting the most out of it remain slim. Having specific, well-trained, and well-respected employees ramp up enthusiasm for the new normal has proven particularly useful.

On-Demand Microlearning

Rolling out bite-sized digital classes that incrementally build an employee’s AI expertise can especially appeal to operations that cannot afford to lose productivity to weeks of dedicated training.

Executive Modeling and Buy-In

The support for an AI solution has to come from the top. Executives need to make it clear to everyone at the company why the organization adopts AI and how it will benefit not just the company’s bottom line but the day-to-day operations of all employees.

The Smart Approach

Industry experts agree that AI’s goal should not merely replace the human element, but enhance capabilities. Whether through automating routine tasks so employees can focus on more complex and creative duties, or by giving them tools to improve their performance, the right education can encourage an organization’s employees to welcome AI with open arms.

Cox Business can serve as an invaluable resource in this endeavor, fostering a learning environment through AI-friendly infrastructure, digital learning, and technology partnerships. Training smartly means training at scale by utilizing cloud platforms, private networks, and reliable connectivity—requirements that Cox Business understands well. Before adopting AI, evaluate the talent readiness of your company, and contact Cox Business to help empower your current staff to make the most of this groundbreaking technology.

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Martin Jones

Martin Jones is a Senior Manager and Editor for CoxBLUE at Cox Business covering business technology, tech trends, news, and related interests including enterprise, small business, healthcare, hospitality, education and more.