Organizations must learn how to use artificial intelligence effectively and responsibly before reaping the benefits of it. However, when implementing AI, a lack of AI talent and skills is a barrier organizations face.

Developing AI literacy throughout the organization is a critical success factor for scaling AI. Organizations not addressing AI literacy will not succeed in creating value with AI.

AI literacy is the ability of people to employ AI effectively and responsibly in context, both business and societal. This includes knowledge about the implications, risks and resulting value and outcomes. It includes understanding the fundamental principles of AI, technology and applications, analytical and algorithmic methods, data and knowledge sources, and ethical considerations. AI literacy, and the required depth of knowledge and competencies across these topics, vary per role of those involved in AI.

Setting up an AI literacy program is often challenging, as the level and speed of adoption of AI varies across the organization with many stakeholders involved, each having different needs in terms of AI knowledge and skills. Many organizations seek to accelerate the maturing of AI literacy among existing and new employees.

There are five steps to creating a roadmap to proactively initiate, design, execute and monitor an AI literacy program that AI leaders can take.

Step 1: Communicate the importance of an AI literacy program to stakeholders and drive awareness

To start an AI literacy program, organizations must build the case for its importance. This case can help obtain a mandate for an enterprise-wide AI literacy program. To gain buy-in for investment in AI literacy, identify, contextualize and communicate key benefits with stakeholders. For example, present AI literacy benefits – focused on those that are the most relevant to the organization – to the board of directors and ask for approval to start the AI literacy program, including funding and staffing.

With AI literacy being closely related to, and overlapping with, data literacy, benefits can be extrapolated from known financial performance improvements. In short, AI literacy is critical to more AI scaling, strategic impact of AI, AI value creation, democratization of AI, effective use of AI, realistic expectations about AI, effective AI engineering, data value realization, and responsible and safe AI.

Step 2: Develop an AI literacy value proposition by connecting ‘learning to earning’

An enterprise literacy program’s overall value proposition is to enable the organization to execute on its AI ambition and AI strategy by maximizing the realization of results.

To ensure the AI literacy program is not too widely scoped and instead focus on the highest value and most realizable outcomes within the AI strategy and ambition, AI leaders should link “learning to earning.” They should create narratives with their teams that connect the specific learning activities needed to realize targeted AI-enabled business outcomes.

Each “learning to earning” narrative identifies specific AI literacy needs for specific employee personas to fulfill prioritized AI use cases. Stakeholders include business managers, HR learning and development teams, talent and organization change teams, affected employees and, particularly, the executive or leader with accountability for the business outcome. This connection between the learning activities and achieving business outcomes should yield the primary success metrics for the AI literacy program.

Step 3: Determine AI literacy needs for each persona group

Regardless of ambition levels, the effective and responsible use of AI requires knowledge and skills for both technical and business or nontechnical roles – anyone involved in the prioritization, ideation, development, use and operations of AI applications.

In collaboration with human resources, assess current AI literacy levels to design a training program that closes each persona group’s skills gaps. The AI literacy program should align with and complement other preexisting data or digital literacy programs.

Step 4: Design and deliver the AI literacy program guided by the AI-era learning manifesto

AI technology, adoption, use, capabilities and associated risks are evolving rapidly with no slowdown in sight, so AI literacy skills development must match this accelerating pace of change. It must also span from relatively basic skills for end users of provisioned AI applications to deeper expert proficiency, such as training machine learning models or other advanced AI capabilities.

Lastly, it must be able to scale up quickly from early adopters to the entire enterprise workforce. AI leaders should therefore adopt outcome-driven agile learning practices proven to develop skills rapidly, scale up across an entire workforce and enable strategic business outcomes.

AI leaders should start with the “learning to earning” narratives from Step 2 that define the highest-priority AI literacy needs to guide the program design. Then, adopt the AI-era learning manifesto principle of “embedding learning in the value delivery flow,” a practice that is two times more likely in enterprises that deliver desired outcomes from learning.

Step 5: Assess AI literacy program impact: Iterate, adapt and extend

AI leaders should regularly conduct a review or retrospective to assess the four previous steps of the AI literacy roadmap. The review should explore whether the program is developing the needed AI literacy to enable business outcomes. This should be combined with a review of data literacy activities, if existing.

The program should also be agile in design with ability to rapidly respond to changing events such as competitors’ AI strategies, business leaders’ heightened interest and new compelling business cases, emerging or undermitigated risks, technical developments and new AI capabilities.

Pieter den Hamer is a VP analyst at Gartner. His coverage includes AI and related topics such as data science, optimization and decision intelligence. Gartner analysts will provide additional analysis on AI and strategic planning at Gartner IT Symposium/Xpo, taking place Oct. 21-24 in Orlando, Florida.

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