training industry

AI-Powered Training Logistics: Enhancing Agility and Efficiency

Artificial intelligence (AI) is opening up whole new worlds of possibilities when it comes to training and retaining employees, which is especially important to businesses today that are struggling to keep pace with rapidly changing training demands brought about by new onboarding and upskilling expectations.

Much of the conversation so far has centered around using ChatGPT and other large language models (LLMs) to accelerate training content production and help curate content for learners. These use cases are promising and are only scratching the surface of what is possible.

These technologies — especially the generative AI programs that show they arrive at conclusions and recommendations — can also revolutionize training logistics for businesses, which will help companies get far more value out of their training operations programs.

Program Optimization

The hot topic today is how AI can be used to create engaging content so that training programs begin to resemble streaming video, immersive games and other experiences that people love.

But what is yet to be explored is the use of AI by company leadership to optimize their organization’s training operations. Organizations are seeing that training plays a critical strategic role at the executive table, influencing and even surfacing critical business decisions. Aligned data architecture and data sources available for analysis are crucial to empowering this capability. Laying this groundwork enables the leveraging of AI tools to deliver rapid-decision support that is designed for specific business key progress indicators (KPIs).

When companies use AI this way, they will have a change-ready planning tool to save time and maximize training operations resources, including equipment, space and instructors. There are many opportunities for optimization based on analysis.

Today, complex logistics and resource allocation decisions are a headache for training teams because these teams must manage far more than just the delivery of learning programs. Before they even get to program delivery, they must fit training time into the normal flow of business, which is no small feat.

Even the most efficient organizations take weeks to schedule and hold trainings. Agreeing to a training schedule means navigating piles of post-it notes, calendars and stakeholders with varying availability. And if there is one small scheduling change anywhere along the line, it’s back to square one. This lost time is more than an inconvenience for most businesses. It can easily mean lost work hours, production time and revenue opportunities.

AI-powered training technology can apply rapid intelligence and problem-solving to many of these routine, time-consuming tasks, such as scheduling training sessions. This can make teams more agile and adaptable to change and free up training teams to focus on more strategic tasks. For example, enterprise training teams spend hours planning and manually booking training schedules every quarter. Most of this time is spent cross-checking spreadsheets and calendars to find the best plan to book instructors and resources. This can be an incredibly daunting task when working from multiple systems in dispersed locations with hundreds of employees.

This is where AI-powered tech can be leveraged to streamline traditionally time-consuming activities. AI can make multivariate decisions and provide reconciled options in a fraction of the time it takes for humans, however many calendars and sticky notes they have working for them. Using AI for training logistics will be a win for businesses.

Getting to the Next Phase

Company leaders will not just want to use AI to create more engaging training content and optimize the training function at their business — they will also want to clearly see how AI is benefitting their organization.

To measure success, they will need a wealth of data that can be made available to AI. But the longstanding practice of offering training programs via single-point software solutions will make this a challenge. It’s also why the C-suite has never had a clear view of the return on investment (ROI) to their organization for investing in training technologies — and why they have been hesitant to invest more in these solutions.

Many disparate, single-point training tools were not created to integrate easily with other programs. Combining the data they generate with other data has been a manual task for training teams, who compile numbers from various systems in a spreadsheet for manual analysis. And time for deep analysis is rare when most training teams already function beyond capacity. Point solutions with siloed data have limited this ability for large-scale training organizations and therefore limited their ability to lead the business from the front position. Historically, the time and resources for such analysis have been a limited luxury or constant fire drill. Technology can now step up to help.

Leveraging an infrastructure platform for training provides the system integrations and resulting “data lake” that is needed to bring data-contributing systems together. Data availability is a core pre-work of effective AI utilization. The more available your corpus of data and the better your data architecture, the better return an AI can give you.

By using the platform approach with training technologies, AI can then analyze data against the organizational KPIs provided by company leaders. This will give teams a significant head start at placing data into appropriate contexts that can then inform rapid decision-making and impact business results. It also shows company leadership why investments in training programs and technologies benefit the whole organization. Training programs must be agile in order to provide for and respond to business growth needs. Speed matters, but it cannot come at the cost of business intelligence. AI can speak to this need.

AI has the ability to do far more than help training teams create engaging content. It can optimize the training function in such a way that days’ worth of manual organizing can be completed in minutes.

But before businesses can realize this potential, they need to digitize their training data, use learning analytics to study it and integrate it with other critical business functions at the company. This will help AI live up to its full potential in the training department.