Danny Abdo, Chief Operations Officer at Skillable.

Training has never been more crucial given the cybersecurity talent shortage, the need for improvement in cloud configuration and demand for experts amid the global AI race. U.S. companies understand that. In 2022-2023, they spent $101.8 billion on training. Yet, a study conducted by my company found that 40% of technology workers feel that their current learning isn’t translating into job performance, and that’s a risk for companies undergoing any kind of digital or AI transformation.

Which, let’s face it, could be every company in today’s AI age. Without the right job-ready skills across an organization, AI efforts could fail to deliver value and the company would have human-made vulnerabilities in their cybersecurity strategy—that could scale as they add more digital workflows and technologies. Indeed, a new report from MIT explains cloud misconfigurations are among the top reasons for the recent uptick in personal data theft.

Traditional learning can’t always keep up.

The simple truth is that traditional corporate learning often isn’t enough to upskill people to the depth needed by most businesses at scale and speed. That’s because it’s primarily knowledge-focused, which does have a time and place in learning cultures—but it cannot be the end-all for business-critical, technical skills.

Many organizations know this because they are relying on buying talent at increasingly high price points. Amid stiff competition for AI talent, organizations are getting creative to acquire the right skills—offering almost seven figures for top AI professionals and buying AI startups. But the supply is drying up, as Will Markow of labor market analytics firm Lightcast points out: “We only have 69 skilled cybersecurity workers for every 100 that employers demand.”

Focus on getting “building” skills right for your business.

So, we need to revisit the “building” part of acquiring the right AI and cybersecurity skills for your organization.

Upskilling the workforce in AI and cybersecurity skills is inevitable. This is not just because the external options for getting the right skills in-house are extremely limited but also due to the need for widespread AI and data literacy. People cannot work effectively alongside or oversee AI models if they don’t have a baseline knowledge of how to use a tool and assess its outputs. Without a fundamental understanding of AI relevant to each person’s role and the business, AI implementation won’t translate into increased productivity, data-informed decisions, competitiveness or any of the other proposed benefits of AI.

Then, we need to look at the cybersecurity side of the house. Again, company-wide skill development is needed. Companies should evaluate and make sure every single person knows their cybersecurity best practices and technologies and how this relates to their role. With potentially everything on the line, focus on making your training ultra-specific to each individual while also validating that they know what to do when exposed to a cyber-attack.

Introduce hands-on learning to your L&D.

I think the answer to both AI upskilling for business effectiveness and cybersecurity for resilience is hands-on training opportunities that put individuals in the moment, showing them how to apply their skills to their jobs and validating that they are ready for real-world challenges.

It can be risky to only offer a traditional learning approach like a content-based learning pathway or video playlist, hoping that this learning translates into real-world application. Even if someone memorizes materials well enough to score highly on a multiple-choice test, they may crumble when putting knowledge into practice.

Giving people the opportunity to consider the real-world scenarios they’ll be up against and play with potential solutions empowers them to really learn. They, and you, as their employer, can then clearly see what they know and don’t know. And if there are gaps, you can surface them and offer specific guidance on what people got right and where they need to improve.

It’s a more surefire path to success than the trial-by-fire approach that many businesses use—and it has the added benefit of helping you assess people’s skills in an unbiased, data-driven way.

Tailor to each skill level.

Bringing a real-world element to your learning strategy makes learning more applicable to every skill level. Tailor your experiential learning activities to a complete AI and technical novice, a data scientist, a cybersecurity professional—and every role in-between.

Training becomes a lot more relevant when you take a tailored approach; you won’t get employee disengagement when someone doesn’t feel challenged by their learning and, critically, people understand exactly how to apply their skills within your organization, your way, using your unique tech stack. So, even if you are fortunate enough to hire someone with the right AI and cybersecurity skills, you can train them in the last-mile application of their skills to your workplace.

Flip the focus.

Look at the hands-on application and readiness of skills, and consider the tasks and work that need to be done. This creates a natural link between learning and work, which many L&D teams have struggled with for decades.

Moreover, it makes it easier to keep up with the rapid developments in AI and cybersecurity because as a need arises (such as a new technology or threat), you can design a hands-on learning environment, such as a virtual lab, that reflects this. People can complete the training, getting hands-on experience in the new tasks they suddenly have to do, with scoring that shows their leaders they are prepared to use their skills on the job.

Other experiential learning options you can consider for your learners include on-the-job assignments, either as stretch projects or temporary redeployments in other departments, where individuals can then practice and prove their skills on real-world tasks.

Another alternative, if your organization cannot risk someone working on live projects, is volunteering—if the skills align with volunteering opportunities. Depending on the skill being learned and practiced, plus your unique business needs like scalability and accessibility, you may use a combination of in-person and online opportunities to upskill, test and validate your workforce.

A final thought. Let’s say that in the next week, you knew that there was going to be a huge cybersecurity attack. What kind of training would you want to offer your people?

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