Daniel Gumucio is the CEO & Founder of AssureSoft, a premier nearshore software development company with development centers across Latam.
Traditionally, companies evaluated talent through visible signals like output, speed and experience. AI is changing both how work gets done and how organizations assess employee value. Those signals still matter, but they no longer tell the whole story.
As automation simplifies routine tasks, adaptability, judgment and systems thinking are becoming stronger indicators of performance. Top employees apply these qualities to improve outcomes beyond their individual roles.
When my company began integrating AI more deeply into our software development workflows, productivity increased as expected. More surprising was how clients began emphasizing qualities in our developers that had rarely been central before. The developers who stood out were not always the fastest. They challenged weak solutions, considered the broader system and improved processes for others. This reshaped how I evaluate talent.
This trend is already visible in the labor market. PwC’s 2025 Global AI Jobs Barometer found that AI-skilled workers earned a 56% average wage premium in 2024 and that required skills are changing 66% faster in roles most exposed to AI. The takeaway is clear: the definition of valuable work is changing fastest where AI has the greatest impact.
Output Is No Longer The Clearest Signal Of Value
Before AI, consistently producing quality work was a reliable talent signal. AI complicates that relationship.
Professionals can now produce more in less time, but volume is less distinctive when these tools are widely available. Leaders must evaluate the substance behind the output.
Did the person understand the problem? Did they recognize where the AI-generated answer was weak? Did they identify the trade-offs? Did they see the risks created by speed?
Organizations need to adjust their evaluation criteria. More output does not always mean more value. It can simply create more material for others to review or correct. The most visible contributor is not always the one creating a lasting impact.
New Job Titles Are A Symptom Of New Expectations
The rise of AI-focused roles shows how companies are redesigning positions around AI fluency, workflow transformation and hybrid skill sets.
Software engineering offers a clear example. Roles such as AI-Augmented Software Engineer or AI Code Quality Engineer reflect a deeper change in what companies expect from development teams. The job now extends beyond writing, reviewing or shipping code to understanding how AI changes the operating model behind software delivery.
The title matters less than the capability it represents. Organizations increasingly value people who can connect tools, teams and outcomes, translating AI capabilities into better processes. That is very different from simply asking someone to “use AI.”
The Best Talent Thinks Beyond The Task
As AI takes over more of the task layer, human value moves closer to the system layer.
A developer who only writes code is less valuable than one who understands how a change affects the product, customer experience, QA process and long-term system health. An operations professional who only completes workflows is less valuable than one who can redesign them.
Systems thinking is becoming a critical talent signal. Top performers identify dependencies and friction points and know where speed introduces risk or automation creates leverage.
Many organizations still struggle to achieve meaningful enterprise impact from AI because value emerges when workflows are redesigned around it. People who improve the systems around tasks will become more valuable than those who only complete the tasks themselves.
Employees Are Changing Their Expectations, Too
This shift goes both ways. As organizations raise expectations for talent, employees are raising expectations for employers.
High-potential professionals want modern tools, meaningful learning opportunities and roles that allow them to pursue higher-value work. They also want to understand how AI will shape their growth, not just their productivity targets.
Microsoft’s 2025 Work Trend Index describes a progression in which AI begins as an assistant, agents later join teams as digital colleagues and eventually humans set direction while agents manage broader business processes. If this is the future of work, employees must learn to direct, evaluate and govern AI-enabled work.
Leading organizations will treat this as a talent development challenge, not just a technology implementation.
Hiring Has To Look For Different Signals
This shift requires leaders to rethink hiring and promotion.
Past experience and tool familiarity still matter, but they can quickly become outdated. Leaders should look for deeper indicators: How did the candidate make decisions with incomplete information? When did they challenge an easy answer? How do they evaluate AI-generated work? What processes have they improved? What trade-offs do they see that others miss?
AI literacy will be important, but it will not be enough. Its value increases when paired with the human skills required to apply it responsibly.
The Talent Definition Is Changing
AI will continue to automate routine tasks. That does not make people less important. It changes which human capabilities matter most.
Companies that recognize this early will hire for judgment and adaptability. They will promote people who improve systems, not only those who complete tasks. And they will create roles that help employees operate above the level of automation.
For leaders, the lesson is clear: talent strategies must evolve beyond traditional signals. Output, speed and experience remain useful, but they are no longer sufficient.
AI is exposing weak talent signals. Organizations that learn to identify real value beyond output will be better positioned to build teams that move quickly while preserving the judgment that makes speed effective.
Forbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives. Do I qualify?