# Shrewd IT hiring strategies have never been more critical > Source: > Published: 2026-08-28 10:01:00+00:00 Major shortages of [qualified professionals](https://www.cio.com/article/4134254/state-of-it-jobs-ai-sparks-rapidly-changing-market-for-skills.html) for key IT roles will lead to huge competitive challenges for organizations that fail to prioritize tech recruiting over the next couple of years, industry observers say. Hiring the right staff has always been a prime concern for IT leaders, but the pressure to find the right candidates has never been higher, with qualified AI, cybersecurity, and data science professionals [especially difficult to find](https://www.cio.com/article/4184685/the-11-hardest-it-roles-to-fill-in-2026-and-whats-changed.html). Worse, those three domains, along with business/IT automation and risk management, make up the top five areas where CIOs are hiring today, according to CIO.com’s [State of the CIO survey](https://us.resources.cio.com/resources/state-of-the-cio/). Everyone appears to be hunting the same scarce resources — a market condition that’s already undercutting enterprise opportunities, [around AI in particular](https://www.cio.com/article/4165232/whats-holding-back-enterprise-ai-shortage-of-talent-cios-say.html). As a result, IT hiring practices over the next 18 months to two years could make or break companies, with laggards risking a huge competitive disadvantage, experts suggest. Organizations need to think both about hiring outside workers and [retraining existing employees](https://www.cio.com/article/4196325/it-leaders-prioritize-addressing-ai-skill-concerns.html) to cover gaps, says [Adam Wachtel](https://www.clickboarding.com/about-us/adam-wachtel/), CTO at employee onboarding platform provider Click Boarding. IT leaders should think wholistically about [building capabilities in their teams](https://www.cio.com/article/4190638/build-or-buy-smart-cios-know-the-answer-for-ai-talent.html), he suggests. “The market for pure AI specialists is volatile and expensive and keeps shifting,” he notes. “What separates organizations right now is whether they’re building AI capability into the team they already have or waiting to buy it fully formed from outside; those building make progress while those waiting are falling behind, and it’s only becoming more expensive.” There are major implications for organizations that fall behind, Wachtel adds. “The most immediate risk is technical debt you can’t see accumulating until it’s expensive to fix,” he says. “I’ve lived through rebuilding a team and a platform from a thin, overstretched state, and the lesson that stuck with me is that understaffing or misaligned hiring fails quietly through slower development, more fragile systems, engineer burnout, and more time fixing versus building — it’s not fun for anyone.” There are several implications for botched hiring efforts, notes [Henry Vassal Jones](https://www.linkedin.com/in/henry-vassall-jones-emapta/), CIO at outsourcing provider Emapta. “If you don’t have the people and capabilities to execute, transformation slows, product releases get pushed out, and existing teams [carry more of the burden](https://www.developernation.net/blog/state-of-developer-wellness-report-2024/),” he says. Critical AI initiatives can fail without the right people in place, Jones notes. “Companies can invest heavily in AI platforms, but without people who understand the business processes, data, governance, and security behind those tools, much of that investment will never reach its potential,” he says. Jones agrees that employee training, as well as strategic hiring practices, plays an important role in keeping organizations reaching their capacities. Successful companies will broaden their approaches beyond constrained local or regional talent markets and develop their existing people, he says. “Those that don’t risk seeing the gap between what the business needs and what their technology teams can deliver continue to widen,” Jones adds. “For CIOs and CTOs, this is no longer simply about filling open positions; it’s about building a talent model that gives the organization access to the right capabilities when needed.” When it comes to developing that talent model, [Konstantinos Dolkas](https://www.linkedin.com/in/konstantinosdollkas/), CTO of cybersecurity upskilling and workforce development company Hack The Box, calls for IT leaders to broaden their geographic horizons. While talent is distributed, most hiring strategies still aren’t, he says. He also advocates [employee upskilling](https://www.cio.com/article/3998201/cios-get-serious-about-closing-the-skills-gap-mainly-from-within.html). “Recruiting externally can’t be the entire solution,” he says. “Build the majority, buy the scarcity. That could mean a few genuinely senior external hires to set patterns and mentor.” Given shortages in AI and cybersecurity skills, hiring leaders should also focus more on demonstrated skills from outside hires than the titles they’ve held, Dolkas suggests. “The best strategy is to hire for demonstrated ability, not credentials,” he says. “Put candidates in a hands-on environment and watch them work. It’s the only screen that survives contact with reality.” Assessing AI security skills can be particularly difficult in a field that reinvents itself every quarter, Dolkas adds. Another challenge is separating genuine AI fluency from tool familiarity: “Prompting an assistant is not the same as securing an agentic system,” he says. In addition to building from within, smart IT leaders are focusing on the capabilities their organizations need one to three years from now, says [Tom Ioele](https://www.linkedin.com/in/thomas-c-ioele-9aa0452/), CEO at recruiting firm TalentBridge. IT leaders involved with hiring decisions should think about building talent communities before the demand exists, he says. Organizations should continuously [identify and engage](https://www.cio.com/article/3841198/it-leaders-whats-the-gameplan-as-tech-badly-outpaces-talent.html?utm=hybrid_search) with people who have the skills they know they will need, instead of starting to search when a requisition opens, he advises. “The biggest mistake companies make is treating hard-to-find technology talent like a traditional requisition,” Ioele says. “By the time an AI engineer, cybersecurity expert, or data scientist hits the open market, every company is competing for the same person.” The companies that win won’t necessarily have the largest recruiting teams, but they will have the best talent intelligence and the ability to activate it faster than their competitors, he adds. Successful organizations will build talent capacity before they need it, he says. “We’re entering a market where the skills companies need are changing faster than traditional workforce planning cycles,” Ioele says. “Organizations that continue operating through a simple post-a-job, screen resumes, fill-a-seat model will constantly be reacting to yesterday’s demand.” **See also:**