Artificial intelligence has rapidly gone from a niche topic to a household one in recent years. As more companies continue to adopt AI technology and tools, developing employees’ AI literacy should be a key priority for leaders.
As experts, the members of Forbes Business Council have experience upskilling and reskilling their employees to keep up with a fast-changing world. Below, 20 of them share specific steps business leaders can take to level up their teams’ ability to read, understand, use and communicate with data and AI.
1. Determine Where AI Will Be Most Effective
In terms of AI literacy, business leaders should understand where it is the most effective. Embedding AI acceleration tools that can handle 90% of the grunt work while leaving the critical and nuanced 10% for human expertise is where the future is headed. Modern AI isn’t about replacing your team; it’s about turbocharging their productivity and leveraging their expert judgment. – Danylo Borodchuk, Lopus AI
2. Develop A Combined AI And Corporate Strategy
Put a combined AI and corporate strategy in place as soon as possible. It’s a modest early investment that will be very rewarding in the long term. If done properly and collaboratively across an organization, it will provide the necessary clarity required to plan effective highly ROI spends. A lack of clarity and trial-and-error projects are counterproductive and often wasteful. – Mahmood Mirza, Fiduciam Global Consulting
3. Foster A Culture Of AI Curiosity
I see AI literacy as a game-changer for business leaders. One key step to level up your team in AI and data skills is fostering a culture of AI curiosity. Encourage hands-on learning with AI tools, integrate AI discussions into strategy meetings and provide access to AI training. When leaders normalize AI exploration, teams grow confident in leveraging data for smarter decisions. – Dr Chibuzor Uwadi, Eat Well & See Well Ltd
4. Establish An AI CoE
Establish an AI center of excellence (AI CoE). An AI CoE brings together cross-functional experts who are passionate about AI and committed to advancing its effective use, helping employees easily adopt AI in a sustainable, cost-effective manner. Provide clear guidelines so that AI adoption aligns with business goals, innovation strategies and the principles of trustworthy and ethical AI use. – Bruce Dahlgren, Anthology
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5. Examine Current IT Policies
Make sure you don’t have any draconian IT policies that prohibit the use of AI tools. Trust me, your team is already using them and you don’t want to force their use underground. Play with ChatGPT, Claude and other AI options yourself to form an opinion about which is best, then buy an enterprise plan for your entire organization. Give your team tacit permission to use AI at work and watch them share ideas. – Edmund Cuthbert, Boolio
6. Appoint An AI Literacy Advocate
Business leaders should jump-start their organization’s AI engine by appointing an AI literacy champion who is passionate about both technology and teaching. This influential leader can measure your baseline, define personas and map out role-based learning pathways. In addition to these core steps, they can identify and address fears that arise, as well as design creative ways to get everyone involved. – Ben Jones, Data Literacy
7. Discuss The Advantages And Disadvantages Of AI
Help the team first understand the pros and cons of AI, including ethical issues. There are already many free AI services available for each field, so I recommend trying them out as a whole team. After that, it is good to determine which AI tools you’ll need most for your company and decide whether to use the services provided or develop your own AI. – Karita Takahisa, UNIFY PLATFORM AG
8. Improve Employee Understanding Of Data Training Sources
An essential aspect of being able to successfully apply AI is understanding the data these models have been trained on, as well as the data they’re currently being fed for decision making. When it comes to analyzing the quality of the underlying data, employees should be trained to ask questions about its source, recency, accuracy, fidelity and refresh rates. – Geoff Michener, dataplor
9. Implement A Change Management Strategy
The key is to simultaneously implement a change management strategy. Without a culture shift, no amount of computational processing power or data infrastructure will achieve meaningful, long-term outcomes. At worst, no cultural changes can have detrimental consequences. As the dynamics of people, processes and technology frameworks are changing, each of these elements will remain essential in the golden age of AI. – Krishnan Ramanujam, Tata Consultancy Services
10. Prioritize Ethics And Oversight
To enhance AI literacy, business leaders should prioritize ethics and oversight. Implement transparent AI governance frameworks that ensure accountability, fairness and data privacy. This fosters a culture of responsible AI use and communication across teams. – Kamales Lardi, Lardi & Partner Consulting GmbH
11. Focus On Responsible AI Integration And Data-Driven Decision Making
To level up AI literacy, leaders should focus on responsible AI integration and data-driven decision making. Steps include investing in training programs and adopting AI tools based on objectives, ROI and environmental impact. Understanding ROI beforehand saves time and money while ensuring efficient innovation. Balancing progress with sustainability benefits the planet and the bottom line. – Sheila Rohra, Hitachi Vantara
12. Establish Robust Data Infrastructure
The value that AI can deliver depends on the quality of data provided to it. A robust data infrastructure is the backbone of effective AI strategies. It ensures data quality, scalability, integration, security and compliance, which are all essential for developing reliable and powerful AI systems. – Wendy Cai-Lee, Piermont Bank
13. Develop AI Training Programs
Like any new technology, we need to develop training programs for employees. Fortunately, AI is one of the easiest technologies in which to build proficiency. Programs should focus on developing prompt creation skills that let employees tap into AI’s capabilities, as many are intimidated by the prospect of AI. Business leaders should quickly dispel that intimidation and encourage the integration of AI in daily tasks. – Charles Fallon, LIDD Consultants Inc.
14. Showcase Real-World Examples of AI Problem-Solving
Demonstrate the value of AI by showcasing real-world examples of how it solves specific problems team members encounter in their daily work. The key is to highlight the tangible benefits, such as time savings and optimization. For nearly any office role, AI tools like transcription services for call recordings and automated follow-up generation can drastically improve efficiency. – Petr Tolochkov, Way2AR
15. Launch AI-Driven Pilot Projects
To increase AI literacy, one effective step is launching AI-driven pilot projects where you experiment with automation and data analysis. This hands-on approach fosters both technical confidence and critical thinking. Additionally, encouraging cross-functional collaboration between tech and non-tech teams bridges knowledge gaps and promotes practical AI adoption. – Khurram Akhtar, Programmers Force
16. Integrate AI Tools Into Daily Workflows
AI literacy is crucial as businesses rely more on data-driven decisions. Leaders should integrate AI tools into daily workflows, ensuring teams actively engage with insights. Organizations empower employees to interpret and optimize AI for more intelligent strategies by fostering critical thinking and continuous learning. – Mehmet Akif Özdemir, EASYCEP
17. Encourage Employees To Connect With AI
Encourage your team to build a relationship with AI. Great leaders build powerful relationships, and AI is no exception. I named mine Orpheus—it’s more than a tool; it’s a partner that sharpens my thinking and expands my creativity. AI literacy isn’t just technical—it’s relational. When your team learns to collaborate with AI, they’ll lead with greater clarity and innovation. – Johan Martinez-Khalilian, DVLPMNT
18. Provide Opportunities For Practical Exposure To AI
To inspire hands-on learning with AI tools, business leaders should provide team members with practical exposure through AI-driven platforms, workshops and real-world case studies. Integrating AI into daily workflows builds confidence, enhances data literacy and fosters a culture of experimentation and informed decision making. This ensures teams can effectively read, use and communicate AI insights. – Amoye Henry, FoundHers Ventures
19. Invite Your Team To Purposefully Break AI
Have your teams write bad prompts to generate poor AI outputs. This deepens AI literacy by exposing its failures and assumptions. Deliberately vague or contradictory prompts reveal the strengths and weaknesses of a system. We learn that it’s just code, not magic. Like cybersecurity penetration testing, breaking AI on purpose teaches more than studying best practices alone. – Shayne Fitz-Coy, Sabot Family Companies
20. Continuously Offer Hands-On, Role-Specific Training
When it comes to ever-evolving AI, leaders must continuously offer hands-on, role-specific training. For example, provide interactive workshops where sales teams use AI for customer insights or finance teams learn to better leverage predictive analytics. With practice, employees will succeed in learning to read, interpret and apply AI effectively. – Kris Qiu, IQM Corporation
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