These days, artificial intelligence (AI) seems to be everywhere. New use cases and tools emerge every day, and there are still untapped opportunities — especially for learning and development (L&D) leaders looks for ways to make processes easier, get work done faster and improve L&D outcomes within their organization.

AI is more accessible than ever before, but you need to build a strong business case and optimization plan to go beyond the experimental phase and start to see true business outcomes. Even if you’re still learning more about working with AI, there are a few proven strategies you can lean on to join the race and get ahead of the competition.

What Is an AI Agent?

AI agents, also referred to as agentic AI, are systems or programs that can make decisions and act autonomously based on their specific environment, typically to achieve certain goals. They often use machine learning, natural language processing or other AI techniques to work through what is sometimes referred to as an “agent loop.”

An AI agent begins this loop by perceiving its environment and user behavior, then using its tools to decide what to do next (and act upon this decision) to achieve the established goal. It can also improve over time from model updates, behavior updates, user feedback or new data that comes in — all of which better inform its strategy to serve the user’s needs.

Here’s an example of how this might look in action:

• The AI agent notices a learner is struggling with a particular question or module.
• The agent decides to simplify the learning path and offer reinforcement opportunities better targeted to the learner’s capabilities and growth.
• It may respond to the learner with a message inspiring them to keep going and notifying them of the new path.
• It can also alert managers about these changes to help them track and stay informed on the learner’s needs.
• The AI agent then continues to track which of its actions resulted in improved performance through continued user input and data, which guides the agent’s strategy over time to better refine decision-making and improve outcomes.

This is one example of many. AI agents can also be used by leaders to assist with brainstorming, content gathering and so much more. As Ron Zamir, CEO of AllenComm, said, “Many learning leaders believe they need specialized AI products, but they overlook how learning services can help them align their L&D strategy with the organization’s overall approach to AI and technology.”

What’s exciting is that even AI beginners can create them. Better yet, your organization may already have access to tools like Microsoft Copilot — and even encourage teams to build conversational bots or task agents to support work and integrate AI into the learning space.

But before you jump in, it’s critical to understand what AI support you, your organization and your learners need to thrive.

Uncover the Need

The more you understand what’s required, the better prepared you are to build a case for AI support and investment.

Start by asking yourself these questions:

• What organizational goals do we have this year?
• What matters most to stakeholders?
• What processes currently take a lot of time or use more resources?
• What tasks could I personally use help with?
• What upcoming projects might benefit from a new AI strategy?
• How might learners benefit from AI agents embedded in the learner experience, such as through more personalized learning paths or guided support?
• What key performance indicators (KPIs) relate to learners’ needs?
• How might AI better target these KPIs?

Take note of any answers that stand out to you and dive deeper into any areas where you feel you need to learn more. Check with your peers (and your competitors) to see how AI is changing the way they work or review common use cases for your industry to better envision the benefits and results you can expect.

AI agents can help businesses improve operational efficiencies, reduce costs and provide better support for employees, boosting their confidence and increasing retention.

Yet, these examples only scratch the surface of what’s possible with AI. That’s why it’s important to get involved now to begin building an AI infrastructure uniquely tailored to your organization. To do that, you need to understand what’s currently possible with the resources you have — and where you may need to upskill or research additional investments to get the most out of your strategy.

Assess Your Current Capabilities

There are three main areas to assess when looking at your organization’s current AI capabilities: data readiness, team readiness and technical feasibility. Let’s look at each.

Data Readiness

Identify your data sources and any considerations related to your organization’s data practices. If you regularly work with protected information, you’ll need to understand how to protect data when allowing AI to access a particular source. An agent will only pull from approved sources, so vetting these sources early — and working with your tech team to ensure the AI can ethically access this information — will protect your customers and your business.

On the other hand, you may also find that you don’t have as many sources to pull from as you’d like. In this case, you can expand to trusted public sources aligned to your needs.

Team Readiness

While some of your team members may already use AI every day, others may have little to no experience. Identify key individuals who can act as “AI agent champions.” They may create, integrate or train AI agents to better perform functions unique to your needs, or they can rally other team members around the exciting possibilities AI brings. These champions can also guide others in upskilling their AI capabilities as needed so that everyone can become a champion.

Alternatively, if your team is smaller or lacks AI experience, consider partnering with a specialized L&D staffing agency to temporarily fill these gaps — and train your team — early in the transformation.

Technical Feasibility

There’s a lot to unpack with technical feasibility. What systems will be prevalent in the future? How will AI impact available platforms, especially for L&D? No one knows the exact answer to these questions, but one thing is certain: adopting new technology incrementally helps you stay flexible in handling what’s ahead while bringing AI agents into your workflows.

If you’re not sure what systems your organization currently has in place, connect with an expert who does. They can explain current technology, its compatibility with AI agents, provide insights on experimentation, complexity, cost and how to create a roadmap to adopt AI technology.

Clearly articulating your organization’s data readiness, team readiness and technical feasibility is paramount in building your case, earning buy-in from stakeholders and becoming an AI-ready organization.

Build Your Case

Not all AI agents are created equal. Some are more complex, which makes them more expensive. On the other hand, simple models are more cost effective, but they have less functionality. What matters most is finding an AI agent solution that’s compatible with your organizational and budgetary needs.

But securing a budget isn’t always easy. As you prepare for the AI conversation with stakeholders and key decision makers, be ready to defend:

• Strategic alignment: How the AI agent can support business goals and provide a competitive advantage
• Return on investment (ROI): How the AI agent can result in cost savings (with examples, or a cost vs. benefit analysis to prove claims), as well as an expected time-to-value and scalability outlook
• Operational impact: How the AI agent will improve or disrupt the workflow and integrate with systems, streamline processes, reduce repetitive work, enhance online presence and improve the learner experience
• Data and measurement: How the AI agent will access and gather data, as well as how data can be measured to prove ROI
• Change management: A plan for overcoming risks and hesitations associated with change, as well as any additional learning that will be needed to upskill team members or manage AI systems over time
• Governance strategy: The ability to prove that it will remain secure, remove bias, act in fairness, be transparent and uphold learner rights in every interaction
• Use cases: Examples of how others in your industry have seen success using AI tools and technology, and how your organization can achieve similar or better results

Luckily, you don’t have to do it alone. Along with other leaders and teams in your organization, you can connect with an advisory partner for support — whether you need additional L&D expertise or tech specialization.

For example, Delta Air Lines and many other large enterprises have consulted with partners like AllenComm to complete a technical analysis, get recommendations for optimizing their tech stacks and bring solutions to life. When choosing a partner, research companies that have first-hand experience in approaching the challenges and opportunities unique to AI integration and be sure to ask for references from their current clients to better visualize what your partnership will look like and what they can do to make your life easier.

Take the Next Step

It’s clear that AI is here to stay. L&D leaders who aren’t adapting risk falling behind — but it’s not too late to catch up. Personalized AI agents will help you transform not only the learner experience but also how your teams work and collaborate every day. This AI readiness enables you to reduce costs, upskill team capabilities and compete with the best as the world continues to evolve.