AI-first thinking doesn’t just spring out of a vacuum. Leaders and employees need to adopt an AI-first mindset that prepares everyone for the changes ahead. This makes training and education about AI more important than anything – and where any AI-first efforts are most likely to get bogged down.
Among students, 65% say they had not had the opportunity to take an AI-specific or AI-inclusive courses at their universities, according to a student-run survey published in EdTech. Only three percent felt very confident that their education would help them secure a job in a field involving AI.
AI education is still lacking for current employees as well. While the percentage of workers using AI for their jobs increased from eight percent in 2023 to more than one-third (35%) as of this spring, only 31% said their employer-provided training on AI tools, according to a survey released by Jobs for the Future. In addition, AI use appears to an individual endeavor, with a majority (60%) reporting using AI primarily for self-directed learning.
The importance of education and training to prepare organizations for an AI future is emphasized by Adam Brotman and Andy Sack, in their latest book, AI First: The Playbook for a Future-Proof Business and Brand. An AI-first policy cannot move forward without education and training, said Brotman, former chief digital officer at Starbucks, and Sack, former adviser to Microsoft CEO Satya Nadella.
“An AI-first mindset requires a commitment to ongoing education about AI technologies and their potential applications,” they wrote. “It encourages experimentation and learning from both successes and failures, ensuring that teams stay ahead of technology advancements.”
Such programs should begin with programs “to build proficiency across the organization. These programs should cover AI basics, applications, and potential impacts on various business functions.”
Ultimately, AI education and training smooths the way for “proper governance and process for scaling AI within your company,” they added. “You can’t effectively advise the company on an appropriate AI use policy or help prioritize potential AI pilots if you don’t have a basic understanding of how the foundational AI systems work, versus still needing to improve, or the variety of capabilities and workflows that stem from AI.”
Brotman and Slack outline the progression for both individuals and their organizations – from experimenting with AI to building an AI-first culture:
- AI literacy: Individual use reigns at this stage. For individuals, it means use of AI “for basic search and information retrieval,” the authors stated. Employees may start by “drafting simple emails and blogs with AI assistance.” Organizationally, the first stage of AI literacy is to use it for simple cost-cutting. Additional functions include implementing AI for basic content creation and customer chatbots.
- AI proficiency: Individuals start using AI for more complex tasks “such as custom GPTs for specific purposes, such as study aids or personal projects.” Developers may start developing customer AI applications as well. From an organizational perspective, AI is adopted for workforce automation and ideation. AI is employed for advanced content creation and detailed customer interaction. AI also gets integrated into various departments to enhance productivity.
- AI fluency, or ready for AI-first approaches: At this more advanced stage, individuals demonstrate a capability to “innovate with AI to create innovative solutions,” as well as “use AI to enhance personal projects and productivity significantly,” they explained. At this point, people also “develop a deep understanding of AI capabilities and limitations.” Organizationally, AI gets used extensively for strategy, margin improvement, and competitive differentiation. Organizations that have achieved greater AI fluency leverage AI for strategic decision making and resources allocation, innovate to a greater degree, and “achieve significant impacts on business margins and market position through AI.”
Notably, an AI-first mindset also borrows from the “lean” approach to management, emphasizing “continuous improvement and innovations by building products that customers want through interactive cycles of build, measure, and learning,” Brotman and Slack pointed out.
AI-first lean thinking “starts with identifying the core problem that needs solving and developing a minimum viable product to test hypotheses. Lean thinking is about reducing waste in processes, understanding customer needs through direct feedback, and pivoting strategies based on data and insights.”
