Outdated modes of communication and knowledge sharing are seriously crippling team productivity. On average, employees are wasting 5.3 hours per week waiting for information, and delays to knowledge transfer are causing businesses to lose $44 million in annual productivity.
Moreover, in a globalized and digitalized world, teams are often scattered across locations. Remote work is expected to grow by 25% by 2030, meaning that seamlessly interconnected team communication is crucial now more than ever.
These challenges can also prevent employees from being adequately and efficiently trained, affecting organizations’ future-readiness. They’re also broadening gaps between departments and undermining collaboration.
However, technology, including artificial intelligence (AI), is helping overcome these hurdles. Here’s how organizations can adopt an AI-forward approach to training and preparing their employees for the future of work.
Applying AI Tools to Enable a Future-Ready Workforce
AI is fast becoming the “company’s shared brain,” that connects people, processes and data. Any AI tools being deployed must be embeddable and interoperable.
There are a wide range of platform options, depending on the use case. Some of these are household names, like Google’s Gemini, which is a virtual assistant that’s able to transcribe, record and summarize meetings. Microsoft has also developed a similar tool — Copilot — that performs similar tasks, saving huge administrative legwork for teams across the board.
In the world of manufacturing, platforms like Kaito Camera, which is well accepted by major manufacturing companies in Japan, are growing in popularity. Factory operations often involve quickly jumping between different tasks, and capturing and transferring all relevant information can be tricky. Connecting these image-capturing tools with AI makes it significantly easier for workers to transfer useful information and knowledge for training purposes, as well as for building up knowledge banks and general updates. That way, staff can ensure all the latest information is available whenever they need it.
These tools are also bridging gaps that often exist between different departments, speeding up workflows. An issue common to manufacturing — that is also shared with industries like construction — is that there’s often a lot of back and forth between crews and office-based departments like finance. As a result, cash flows are compromised, teams are even more stressed out and administrative burdens increase.
Using AI in the mix alongside cloud-based platforms to quickly send and save key information in one place is easing a significant operational and administrative headache. This strengthens productivity, efficiency and cross-department collaboration while reducing friction between employees.
Building the Foundation for AI-Powered Training
Before integrating any technology, organizations must assess their current training frameworks. This is where pain points are identified, which can include factors like amount of time wasted chasing information and the quality of central guidance to help employees on the job.
In manufacturing, for example, organizations often use knowledge banks that workers can access whether they’re on the factory floor or behind an office desk. These help teams access knowledge around processes and machinery on the fly. However, these knowledge banks only work when all the necessary information is available and provided in a timely manner. Any gaps, anomalies or inconsistencies are going to be counterproductive, at best causing confusion and at worst harming workers on the factory floor.
Don’t forget to measure these tools. Effective deployment of AI hinges on pre-defining measurable key performance indicators (KPIs) and goals.
These can include the rate of reducing project delays, faster onboarding, productivity gains and improved skills. Measurable goals are designed to keep teams and technology alike accountable, ensuring consistently strong performance and growth in the right direction.
Alongside these considerations, organizations also need to have a digital infrastructure that is AI-ready. That includes making sure all tools and systems are interoperable. Data also needs to be managed so there are no anomalies, errors or missing information that would otherwise compromise AI output.
Pay close attention to privacy and security, ensuring strong guidance is in place to protect systems from any breaches that will compromise data. Integrating AI comes with its own set of security risks, and these must be addressed before deploying these tools.
Empowering Teams to Adopt AI
The teams working alongside the technology must be familiarized with using any new technologies. AI readiness is a fundamental component of successful deployment.
Employees should not only understand how to use AI tools, but also why they are being used. Hands-on training and workshops are excellent formats to build that familiarity so that these tools are being used with clarity and confidence. An important point to remember is that AI only works with the right human follow-through.
For instance, if an AI platform has been integrated to strengthen health, safety and environment (HSE) management in factories, staff should understand how the system functions and how to interact with the tools. AI tools are often combined with Internet of Things (IoT) devices like cameras and sensors to alert factory workers when a risk arises or to notify managers when risky behaviors are happening. If an employee is alerted by AI that they’re violating a safety rule, they need to know how to respond.
When it comes to virtual use cases, employees should understand protocols around safety and administrative housekeeping. Not all meetings need to be recorded, for instance, but employees should be aware of when it makes sense to record one. Follow-ups are also just as important as recordings, so that absentees have access to any useful information or updates.
Technology is a non-negotiable for shaping a future-ready workforce. AI tools are helping teams foster greater collaboration, become more aligned and strengthen knowledge sharing.
