Upskilling workforces in AI and analytics is pivotal for 2025 competitiveness, yet practical challenges abound, with 46% of leaders citing skill gaps per McKinsey.
This HR Spotlight article compiles insights from business leaders and HR professionals on key hurdles to prepare for.
Experts highlight mindset shifts, fear of displacement, data quality issues, and ethical concerns like bias.
They stress fostering curiosity through real-world applications, tailored training, and human oversight to bridge gaps.
By addressing resistance via empathy, ensuring tool relevance, and promoting continuous learning, leaders can transform challenges into opportunities, boosting productivity and adaptability across industries from healthcare to consulting.
Read on!
Casey Cunningham
Founder & CEO, XINNIX
One of the biggest practical challenges leaders face when helping their teams level up on AI and analytics is making it feel real and relevant. It’s not just about training—it’s about sparking curiosity.
I encourage leaders to create space for people to share how they’re already using AI—at home, at work, anywhere. Personal use often translates into professional impact.
I also challenge leaders to ask their peers how they’re approaching this. You don’t have to figure it all out alone. Chances are, someone else in your organization is already a few steps ahead. Learn from them.
And finally—ask AI! Use it to create grocery lists, build menus, fix issues—get people playing with it. When they see what it can do in everyday life, they’ll be more open to using it professionally.
The goal is to normalize it. The moment they experience that “wow,” the resistance fades. Now they’re in.
Spark Curiosity for AI Adoption
Mary Rizutti
Practice Leader, HR Advisor & Outsourcing
Challenges in AI and Analytics Upskilling
While AI is changing so many aspects of business, with change comes challenges. There is clearly and expectedly a learning curve in this space. Companies are facing the challenge of a workforce that has had limited to no exposure and/or training in AI.
To work effectively with AI, a combination of technical and soft skills is needed. Technical skills such as knowledge of programming languages like Python, Java, R and C++ are commonly used in AI development.
Individuals with backgrounds in computer science, data science, artificial intelligence, robotics, mathematics and statistics and software engineering may possess skills upon which they may rely to begin to understand large language and algorithm model development, as well as prompt engineering (the ability to optimize prompts for AI tools), as an example. may be acquired through self-study.
It’s important for companies to assess the current workforce to help them understand which employees might be suited to support an AI integration process. One initiative many companies are undertaking is to perform a skills analysis on its workforce to identify those in-house who possess the capability to engage in identifying areas where AI may be appropriate.
Companies should also be prepared to deal with the challenge of identifying the application for AI within their companies. Some questions they should consider include: How far down the road should we go with AI? Are there controls in place to test and trust AI’s output? Do we have policies in place to monitor and provide guardrails for individual usage?
These challenges call upon leaders to not only possess, but to also instill and encourage keen problem-solving skills among their teams, to create ethical awareness around AI biases, privacy concerns and the responsible use of AI.
Fostering an environment of continuous learning, adaptability, curiosity, communication and collaboration needs to be a deliberate focus for leaders to enable their companies to travel the AI journey that is ahead.
Assess Skills for AI Integration
Danielle Pickens
Chief Program Officer, Urban Schools Human Capital Academy
One key challenge for education leaders is preparing their workforce to effectively adopt AI and analytics. This goes beyond technical training as it requires a mindset shift toward data-informed decision making.
Educators are the heart of schools, yet many lack exposure to AI tools and face time constraints, making targeted professional development critical.
Leaders must ensure equitable access to technology to prevent deepening disparities, while addressing ethical concerns like data privacy and bias.
AI should be seen as a support, not a substitute, for human judgment. It all starts with a strategic, empowered Human Resource team ready to lay the foundation for continuous learning.
By prioritizing upskilling and fostering an open culture, schools can begin to leverage AI to improve efficiency, accessibility, and ultimately, student outcomes.
Bridge Tech, Human Judgment Gap
Everyone has varying ability levels. Some people learn new tools quickly, while others require more instruction. Training must adapt to these variations. The most effective learning is experiential, using real-world examples.
Understanding data ideas is one thing, but applying them to transactions and property management is quite another. The aim is to close that margin. In addition to teaching theory, I concentrate on demonstrating how analytics enhance decision-making.
Confidence is fostered by promoting inquiry and allowing others to grow from their errors. The team tries new things when they feel encouraged. We can maintain our competitiveness in a changing market with such a mentality.
Overcome Varying Team Abilities
Marco Dewey
CTO, Jazzberry
Prompting is your team’s new secret weapon. Everyone thinks these AI tools are just plug-and-play. Drop in a question, get an answer.
The real power of these AI tools isn’t in their ability to answer a question, but in their diversity in what they can do with that question. AI tools are not a set-in-stone algorithm, they are a dynamic algorithm that can give you custom results if you know how to prompt it.
Leaders need to train their team on the art of prompting. Prompting can be unintuitive, but it will make more sense to your team if you educate them on how these models work under the hood.
Think of prompting as a new kind of literacy, and do not be afraid to experiment; only you know what will work best for your team.
Master Prompting for AI Power
Leaders preparing to upskill teams in AI and analytics must tackle three thorny realities. First, overcoming “grunt work paralysis”—even skilled analysts waste weeks on manual tasks like data cleaning or merging NHS trust mappings.
Tools like SCOTi® AI automate this drudgery, freeing 70% of time for strategic work. Second, bridging the “plain English gap”: Employees shouldn’t need coding skills to ask, “Why did margins drop?” Assistive Intelligence that answers conversational queries (with charts/stats) democratizes data access.
Finally, securing buy-in for “messy data” journeys—teams often stall waiting for “perfect” data. SCOTi’s Schema Sense reverse-engineers chaotic databases and even scrapes missing dimensions, proving ROI while fixing infrastructure.
Compliance remains non-negotiable: Ensure tools like SCOTi operate on-premises/air-gapped for sectors like healthcare or defense.
The real win? Treating AI as a collaborator, not a crutch—it’s why teams using assistive tools see 2x faster insights and 50% higher stakeholder trust.
Automate Drudgery, Free Strategy
Wesley Kang
Founder, Realtor1099Cafe
Honestly, running a tech forward real estate firm showed me how emotion drives adoption more than logic ever could.
People fear status loss more than technology itself and my veteran agents worried AI would erase their market expertise until we reversed the power dynamic. Now they lead our AI testing program, finding new ways to blend human insight with machine analysis.
I’ve also seen that fear hits hardest when AI touches money directly and through countless training sessions, I noticed how quickly agents embrace AI for basic tasks but panic when it approaches their commission structure. We solved this by guaranteeing base pay during the learning phase which let them experiment without risking income.
In all honesty, I believe successful AI adoption starts with protecting people’s sense of value.
Reverse Power Dynamic Fears
Paul Monk
Chief Strategy Officer, Alpha Development
AI technology is developing at such a pace that it will quickly become universal, with little to differentiate the tools used by competing organizations. Most of the value of AI will be delivered in the quality of data, and how each workforce is upskilled & motivated to engage with these new tools.
We initially categorize a workforce into two broad groups – the FOBOs (Fear Of Missing Outs) and the Resistance. FOBOs are anxious to be given access to AI tools & training, while the Resistance try to justify why AI is not applicable to their role, team, or business area. Both need to be acknowledged & engaged by any plan to upskill on AI and analytics.
Upskilling & reskilling for AI should be delivered just like any other transformational learning program – it requires business leader support, active learning, and the opportunity to practice & embed new skills following any formal training.
Once new skills have been acquired, the focus should shift to monitoring application of AI within upskilled teams – including keeping a close eye on “disengaged augmentation” i.e. when an employee working with AI augmentation disengages from their responsibilities and inappropriately allows the AI to complete the task end-to-end.
Ensuring that employees understand their role in augmentation, and are recognized & rewarded for delivering this, is crucial for delivering real change in AI and analytics skills.
Engage FOBOs, Resistance Groups
Dan Gower
Product Studio Lead, Sketch Development Services
I work at a software consulting company that helps enterprises adopt AI. One challenge we keep talking about is that AI was trained on a massive amount of material, and it’s not only the good stuff.
It’s getting better fast, but right now, we have to assume that whatever AI is doing is informed by average work. In other words, check it as you would if an aggressively average employee produced it.
Verify AI Outputs Vigilantly
The HR Spotlight team thanks these industry leaders for offering their expertise and experience and sharing these insights.
Do you wish to contribute to the next HR Spotlight article? Or is there an insight or idea you’d like to share with readers across the globe?
Write to us at connect@HRSpotlight.com, and our team will help you share your insights.
Discover the latest HR Tips and trends with our weekly newsletters!