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If the validity of resumes is any indication, most job seekers over-represent themselves to employers. Multiple studies have shown up to 85% of job applicants have lied on a resume, including overstating their skills, experience level, college degrees and past job responsibilities.
Studies have shown, even after lying to get a job, 88.4% of new employees keep up with the lie stating they can indeed operate equipment or software they can’t. How does Artificial intelligence change the game? Has “fake it until you make it” changed to “fake it until you get caught?”
Performance matters, which is why it’s often said managers don’t care what you know, they care what you do. Skills are, arguably, less durable than they have been in past decades, largely due to the speed of innovation and transformation of processes we use every day in our jobs.
Artificial intelligence, integrated into the business systems we use, has the potential to change what we do even faster than before. But what impact will that have on skills development for human beings? Will greater peer pressure force the labor market to “fake it until you make it,” or will true expertise be valued at every organizational level?
AI in HR
Human Resource Management Systems (HRMS) are increasing, including skills inventories providing organizations the ability to quickly pivot by reorganizing talent already available. At a moment’s notice, skills inventories attempt to answer: Can we do business differently with our current employees or the talent available in the labor market?
The same skills inventories enabled with AI decision-making capabilities can also impersonally conduct reductions in force, at scale, as organizations fail to keep pace with market conditions. AI has many potential uses for HR professionals; however, its deployment has extraordinary cultural implications for organizational trust and transparency.
Skills inventories provide data capable of unlocking a great deal of future potential for individuals. Open skills verification systems that leverage digital credentials can also make recognition of training and experience portable from one organization to the next. For individual employees, these systems offer a lot:
Structured learning paths create clarity for promotion
Mastery of skills is recognized in the marketplace
Skills hold currency-like value for future opportunities
Dashboards illuminate trends in technology, processes and innovation
Perception that the system is in control over people
Promotes gaming the system rather than deep investments in skill development
Potential to recommend skills that are irrelevant
Creates role requirements that prohibit applicants from growing after hiring
The pace of innovation makes continued education and investment in personal growth an important value in the labor market. Organizations that invest in employee training programs scored far more favorably by today’s workforce when comparing job opportunities.
AI as a shortcut to skills acquisition and experience
Generative AI systems have shown real early value — from creating ads, writing original copy, summarizing and reformatting proprietary data with insights, to writing lines of software code. There is no doubt, AI systems can aid human performance, especially in terms of speed to creation.
The number one in-demand skill over the next year might very well be mastering new generative AI systems as they come online. However, early results show that domain knowledge is really important when querying systems for output. That is to say, people with experience ask AI systems better questions. And people with experience can validate both the relevance and accuracy of what an AI system returns.
Skill and experience have value. Verified skill and experience are gold.
Proprietary data and competitive advantages
For argument’s sake, let’s assume your organization hires several less-than-truthfully skilled employees who do great work using generative AI solutions. Great work is valuable. Who else has access to the value your new employees created?
AI systems need training data to prime the pump and refine the perfect answer to a query. Your organization’s core proprietary data may be training commercially available AI systems, refining its answer not just for your employees but your competitors’ employees. For many professions, using AI systems to refine individual work has the extraordinary potential to be a legal issue and or ethics violation.
Generative AI systems may have made running a business a whole lot harder.
Regardless of how (if at all) AI is integrated into your business, your employees have a significant role to play. Designing experiences that promote authentic interactions and value individual career development will not only make for a more enjoyable environment but highlight strategic risks before data is lost or corners are cut.