Goldman Sachs predicts generative AI could boost global GDP by seven percent this decade.
With stakes this high, businesses can’t afford to obliterate their competitive edge by not equipping their workforce with the necessary AI skills. Yet, 82% of leaders acknowledge that their employees need new capabilities to prepare for AI advancements, while 60% of workers admit they lack the skills to get their jobs done effectively in this era of rapid technological change.
However, according to Gartner®, “By 2027, more than half of chief data and analytics officers (CDAOs) will secure funding for data literacy and artificial intelligence (AI) literacy programs, fueled by enterprise failure to realize expected value from generative AI.”*
We believe these stats underscore a critical question: Is your workforce ready to unlock the full value of AI, including generative AI?
AI literacy goes beyond using tools like ChatGPT — it’s about understanding AI’s role in your organization, leveraging it responsibly, embedding it into workflows to amplify productivity and innovation, and continuously learning and adapting from there. To explore some essentials of AI literacy, let’s break it down alphabetically into the ABCs of AI literacy, a fun overview designed to help analytics and AI leaders build a robust foundation in this critical area.
A: Awareness
AI literacy begins with awareness. Analytics and AI leaders need to enable themselves and their employees to grasp what AI is, what it isn’t, and its capabilities and limitations. AI literacy is a critical need not just for team members, but for leaders as well.
What to focus on when it comes to enabling your teams:
- Understanding basic AI concepts (e.g., machine learning, deep learning, and generative AI).
- Knowing common use cases, from automating workflows to generating insights.
- Awareness of ethical considerations, such as bias and data privacy.
B: Bias and Responsibility
AI is only as good as the data it learns from, and biases in AI systems can perpetuate unfair outcomes. Building an understanding of bias in AI models and promoting responsible use is vital.
Key questions to explore:
- How can we identify and mitigate bias in AI tools?
- What policies should be in place to ensure responsible AI use?
- Is there diverse representation in AI development teams?
Example: Training employees on Responsible AI guidelines ensures tools like generative AI are deployed in ways that align with organizational values and regulatory requirements.
C: Collaboration
AI literacy isn’t just for data scientists — it’s for everyone, including leaders. Encouraging cross-functional collaboration ensures AI is integrated seamlessly into various parts of the organization. Here, analytics and AI leaders should promote collaboration between their teams, IT, and the business teams, as well as train employees on how to partner with AI to augment their expertise.
To ensure collaboration for AI literacy, executives can create AI champions in each department, develop interdisciplinary AI project teams, encourage knowledge-sharing platforms, and design collaborative AI skill-building initiatives in dedicated AI literacy workshops and mentorship programs.
D: Data Literacy
AI thrives on data. Without foundational data literacy, employees may struggle to understand how AI systems make decisions or how to improve those decisions.
Essential skills:
- Knowing baseline data collection and preparation techniques, as well as how to evaluate data quality.
- Understanding the lifecycle of data in AI systems.
- Recognizing the importance of data and AI Governance and security.
Executives can cultivate these skills via micro-learning modules, hands-on data analysis workshops, interactive data visualization training, and certification programs.
E: Experimentation
AI literacy also means fostering a culture of experimentation. Employees should feel empowered to explore AI tools and integrate them into their work. Practically speaking, analytics and AI leaders can offer sandboxes and low-stakes experimentation zones for employees to test AI tools and share success stories to inspire confidence and innovation.
The Business Impact of AI Literacy
Organizations that invest in AI literacy programs see tangible benefits:
- Improved Productivity: Employees understand how to integrate AI into workflows, saving time and resources.
- Enhanced Decision-Making: Teams leverage data-driven insights to make more informed strategic choices.
- Stronger Compliance: AI-literate employees reduce the risk of data leaks and ensure responsible use of AI tools. Related, the more data scientists and data builders know and learn about bias reduction in model building and management, the more fair and responsible models will be. AI literacy also helps leaders decide which projects to greenlight based on a risk, value, and feasibility implementation framework.
3 Quick Tips to Get Started
- Assess Your Baseline: Use surveys or workshops to evaluate the current AI literacy level in your organization.
- Design Tailored Programs: Create training initiatives suited to different teams’ roles and needs.
- Measure and Iterate: Use KPIs like adoption rates and productivity metrics to assess program success and refine as needed. The tangible benefits or outcomes generated per team/function as a result of the training should also be used here (such as increased productivity, innovation, or financial returns).
The Bottom Line
AI literacy is no longer optional — it’s a strategic imperative. By embracing the ABCs of AI literacy, enterprises can ensure their workforce is equipped to navigate and thrive in an AI-powered world.
Be on the lookout for our upcoming AI literacy blog series on what AI literacy means more specifically to the CHRO, IT executives, and data executives.
*Gartner Press Release, Gartner Predicts More Than 50% of CDAOs Will Secure Funding for Data Literacy and AI Literacy Programs by 2027, January 29, 2024, https://www.gartner.com/en/newsroom/press-releases/2024-01-29-gartner-predicts-more-than-50-percent-of-cdaos-will-secure-funding-for-data-literacy-and-ai-literacy-programs-by-2027. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.