Continuously Upskill Your Team

#LeadershipInTheAgeOfAI

In this era of humans working with machines, being an effective leader with artificial intelligence (AI) takes a range of skills and activities. In this series , I provide an incisive roadmap for leadership in the age of AI.

With AI, standing still means being left behind. Part of maintaining enterprise momentum and value with AI is ensuring stakeholders throughout the organization have the skills and knowledge they need to contribute to AI ideation, development and governance. Given the pace at which AI types are maturing, maintaining the right skills to guide enterprise AI is an ongoing priority. For business leaders, the call is to establish the importance of up-to-date AI skills across the workforce and then create opportunities to help AI stakeholders acquire them.

Importantly, AI stakeholders are not only the data scientists and technologists. They also include executives and employees from the lines of business, and each requires different skills and knowledge according to their role.

While data scientists and AI engineers require highly technical skills that keep pace with AI developments, line of business employees need to understand AI functions and be able to use AI in the context of their work. Marketing managers need an appreciation for how AI can be used in customer engagement and personalized communications, while back office users are faced with an ecosystem of technologies and enabling enterprise platforms (e.g., enterprise resource management, cloud services, AI-as-a-service).

Recognizing that upskilling tactics need to be tailored to the employee’s professional role, there are some overarching approaches that can set the business on the path to continuous skills development.

Nail down the basics.

AI literacy is a foundation for skills building and continuous learning. The workforce needs a working understanding of what AI is, how it functions, the kind of business outcomes it can enable and the risks that may arise.

Highly mature technologies (e.g., personal computers) may only require a one-time literacy course, but AI is different. It is changing rapidly, with new kinds of models emerging and the capacity and scale of those models only growing.

In this, AI literacy is a moving target. Business leaders may consider including AI literacy as a regular part of recurring role-specific training, and they may also find ways to incentivize employees to conduct independent learning via the wealth of literature and lectures available.

Promote knowledge transfer.

The organization’s technologists (e.g., data scientists) are prized subject matter experts who hold a deep understanding of how AI works, its potential and its limitations.

Establish channels connecting the technologists with others throughout the organization. Create regular opportunities for all AI stakeholders to share knowledge (e.g., internal workshops or presentations) and capture the knowledge in documents, summaries, recordings and other media that employees can explore as a part of continuous upskilling.

Follow the trends and research.

Given how fast things can change in the AI field, there is no shortage of new research, best practices, case studies and risk analyses. Growing skills takes, in part, new knowledge.

Business leaders can promote this by offering internal communications identifying important AI developments and sources for further learning. When the workforce is encouraged to keep up with AI as it relates to their professional role, they can gain greater awareness of the kinds of skills needed for their work.

Provide a sandbox for hands-on learning.

Learning through experience can equip employees with greater insight and confidence in using AI. Internal sandboxes allow stakeholders to experiment with AI tools, explore their capabilities and risks and learn by doing in a consequence-free environment. Sandboxes could be used to try out new types of AI, such as a commercial large language model, and they could also be used for proprietary AI applications or copilots that employees need time and experience to master.

Champion collaboration.

Promoting up-to-date skills is ultimately a matter of business culture. When AI is prioritized and stakeholders are encouraged to take part in ongoing learning, it can spark creative ideas and support responsibility and accountability in AI decision-making across the business.

Over time, it creates an environment in which stakeholders are not forced into continuous upskilling, but instead, they elect to focus on skills building because they appreciate the vital importance of their work. How a collaborative culture manifests is necessarily specific to the organization and its AI ambition. The task for business leaders is to set the entire enterprise on a trajectory to that end.

These tactics equip stakeholders with the knowledge and skills to take part in AI application and governance. To understand the importance and urgency, consider the impact of generative AI models that can create text, images, audio, video, computer code and 3D models. This transformative type of AI is different in many ways from more traditional machine learning models, raising new considerations for output validation and keeping humans in the loop as generative AI begins to accomplish cognitive tasks that used to be the sole province of human thought.

Contending with today’s models, the power of generative AI, and whatever groundbreaking innovations are still to come, means setting up the workforce for success by giving them the opportunities to continuously build skills for the age of AI.

Originally published at https://www.forbes.com/sites/forbesbusinesscouncil/people/beenaammanath1/?sh=33cfc0b2bd3e