The explosion of artificial intelligence (AI) in the workplace has added pressure to everyone’s career. But one could argue that learning and development (L&D) leaders are feeling double the workload and responsibility. They are the ones who not only must train others to use AI but also adopt AI themselves to help in this process. This includes using AI to generate content, but also to plan strategies, restructure assessments, address ethical concerns and develop governance and usage standards.
And while AI has been the topic of the year, not every AI project today is proving successful. So, what separates successful AI rollouts from flops? It’s AI literacy, organizational readiness, well-defined short- and long-term strategies and a shift in mindset.
Here are 10 critical things to consider so your organization can adopt AI with purpose and relative ease.
It Starts With Strategic Alignment
1. Put a strategic roadmap together.
Success comes from solid planning. What are you trying to accomplish and how are you going to achieve this? Consider cocreating a strategy with your employees. Their ideas and voices will go a long way when it comes to implementation and adoption.
According to Harvard Business Impact, “49% of L&D leaders expect AI to improve talent development outcomes.” However, when speaking to company leaders, only 42% believe their company offers strong support for employee AI experimentation.
Without a clear roadmap with designated checkpoints and purpose, every new AI product or service on the market will appear shinier than the next, leading to disparate programs and tools that can make things more complicated than necessary.
2. Define your “why.”
When creating a roadmap, don’t forget to ask the most important question: why? If you don’t know why you are looking to integrate AI tools — besides the fact that everyone is doing it — you can easily lose your way. When you understand your organization’s purpose for existing and how AI can support that, you will have an easier time making decisions and getting the necessary buy-in and resources.
Explore Technology and Tools
3. Research tools and determine fit for your organization.
With a roadmap and purpose in hand, you can now begin exploring your options. There are various large language models (LLMs) on the market, each having their own unique set of strengths and weaknesses.
For example, Anthropic’s Claude prioritizes ethics and human-centric interactions. Other LLMs might prioritize content generation, low latency, creativity or efficiency. Do your homework to figure out which works best for your organization’s purpose.
4. There’s more to AI than ChatGPT‑style prompting.
You must recognize that AI is way more than chat or bots. Typing in prompts in ChatGPT is a good start, but it’s just scratching the surface.
The real benefits of using AI for learning purposes are the personalization capabilities, such as role-play simulations with AI-engineered avatars, algorithms that adapt to individual learning preferences and progress and automated assessments. To provide just-in-time support for employees, AI coaches can help refine leadership skills, improve customer service skills, and assist with other relevant power skills for better decision-making and problem-solving.
As if that’s not enough to process, new AI functionality will continue to roll out regularly, making it challenging to keep up. This is where your strategic roadmap keeps you on track.
Change Starts With Your People
5. Determine your stakeholders (i.e., champions, users, sponsors)
Before you can guide your organization through AI adoption, you need a clear picture of who is involved and what role each person plays. Start by identifying your core stakeholder groups: the champions who are excited about innovation, the everyday users who will interact with AI tools regularly, and the sponsors or decision-makers who influence budget and strategic alignment.
Understanding this cast of characters and their level of interest will help you tailor communication, training and expectations so that each group feels informed, supported and invested in the transformation.
6. Determine who’s on board and who isn’t.
Once you know who your stakeholders are, the next step is assessing their readiness for change. Some team members naturally embrace new technology. These are your early adopters and influencers.
Your influencers may already be using AI and can serve as internal advocates for the transition. Lean on them to help build momentum and demonstrate real-world benefits across the organization. Those who are open-minded, but uncertain, will follow once they see peers succeeding and feel the change is manageable.
As for the skeptics, they’ll need empathy, clarity and reassurance from you. Address their concerns directly. Understand their fears and the reasons behind them. Bring them into the conversation early rather than forcing them to adopt. And utilize change management techniques for a smoother transition, but don’t expect overnight success.
Set Up Your Infrastructure
7. Create your own AI protocols and SOPs (i.e., safety, compliance, ethics).
It’s critical to establish guardrails as early as possible prior to integrating AI into your organization. This includes developing internal protocols and standard operating procedures (SOPs) to ensure responsible use of AI.
It’s clear organizations must prioritize psychological safety, inclusion and clear communication in AI rollouts. Consider how your organization will address key risks like bias in training, lack of AI-output transparency, and the ethical use of learner data.
Most organizations are creating their own protocol standards and governance practices. This should include ethics guidelines, bias and fairness testing, data management and security, and more. You may need to create a few new positions to manage all of this as well as research future AI developments.
8. Manage data strategically.
AI is only as good as the data it’s trained on and the data it can access. Before introducing any AI tools, assess the quality, accessibility and organization of both learner data and HR data.
Without intentional data governance, AI tools may yield inaccurate results or fail to provide meaningful insight. Discuss this with your information technology (IT) and data teams early on to define how data will flow into and out of AI platforms. If you are in a heavily regulated industry like insurance or finance or dealing with private data such as in the health care or legal industries, you may want to consider creating your own LLM with heavy guardrails.
Prepare for the Challenges Ahead
9. Educate people on how to leverage the tech.
Training is more than watching instructional videos explaining the use of new technologies. Your training should include exercises that show your team how to use the technology broadly at first, followed by hands-on experimentation for specific use cases.
Instead of setting employees up to learn about AI, enable them to learn with AI. When it comes to utilizing AI-engineered avatars, one option is to leverage the power of AI and virtual reality (VR) so employees can learn in authentic environments.
Beyond initial AI onboarding and training, your teams will need ongoing professional development, but that experience will look different than it does today. Having a detailed and agile development plan will keep you ahead of the game. This is especially true if you have a lot of younger employees looking to you to lead the charge with emerging technology.
10. Anticipate roadblocks and challenges.
Most people love the idea of a set-it-and-forget-it system but that’s just not realistic. Even the most forward-thinking teams will encounter resistance, face roadblocks, and make mistakes.
Some challenges you may encounter are cultural skepticism, employees’ fear of being replaced by technology and tight budgets. That’s why it’s important to proactively identify potential obstacles and include those as well as an action plan to address them in your roadmap. Being reactive to these challenges when dealing with such monumental technological change could deepen resistance and problems.
Final Words to Consider
We can all see AI technology already modifying every industry across the globe. As L&D leaders and professionals, it’s our responsibility to prepare our teams to use the technology properly and consciously. Certainly, some tasks and processes will be replaced by the efficiencies of AI, but AI doesn’t learn or think for you.
AI is driven by statistical models, algorithms and mathematical formulas. This can help in so many instances to do our jobs more efficiently, but AI isn’t going to replace humans anytime soon.
We have our work cut out for us to help our employees and colleagues get on board, but if we explain what AI can and cannot do and the fact that everyone’s jobs will need to be reshaped, it becomes a little more exciting than scary.
