AI in the IT Workforce: Which Roles Are Disappearing and Which Are Emerging?
As AI transforms IT, routine jobs are disappearing while new, high-impact roles emerge. This article highlights the most at-risk positions, the roles rising in demand, and the steps midmarket leaders can take to build an AI-ready workforce.
Artificial intelligence is reshaping how companies use technology and fundamentally changing the roles required to deliver it.
Midmarket companies, already operating under tight budget constraints and lean teams, are now confronting a new challenge: their existing workforce model may not be equipped for the AI era. While automation promises efficiency, it also disrupts traditional IT job functions, introduces new ones, and demands entirely different skill sets and leadership capabilities.
First and foremost on many companies' minds are which roles are being impacted by AI, and what roles do I need to consider to embrace AI fully.
The Disappearing Act: Roles on the Decline
As AI and automation take hold, specific repeatable and routine-focused IT roles are becoming less central:
- Basic IT Support Monitoring, and Administration: AI-driven platforms and chatbots now handle tasks such as password resets, incident triage, and system monitoring and administration.
- Manual QA Testing: Automation frameworks are replacing repetitive test cases that were once managed manually by QA engineers.
- ETL/Data Prep Analysts: As self-service BI tools and AI-powered data pipelines gain traction, the need for hand-coded ETL is diminishing.
- Application/Software Development: AI-assisted coding and low-code platforms are reducing demand for routine coding, shifting developers toward higher-value design and integration work.
According to McKinsey, tasks that take up 60–70% of employees' time today could be automated by 2030—a shift that hits routine IT operations particularly hard. But, this doesn't mean companies can cut roles and hand everything over to machines. It means they need to redefine their workforce to include new, high-impact positions.
Emerging Roles for the AI-Enabled Enterprise
New technologies require new talent. Here are some of the fastest-growing and most in-demand roles in midmarket IT:
- AI Integration Specialists: These professionals translate AI models and automation tools into usable solutions for IT and business teams. They ensure smooth integration across systems while minimizing disruption.
- Data Governance and Risk Leads: With AI comes increased scrutiny. These roles focus on ensuring the ethical use of AI, managing bias, and maintaining compliance with data privacy laws, such as GDPR and CCPA.
- Enterprise, Data, and Workflow Architects: These roles are fundamental to enabling the reengineering of the technical architecture to enable process changes being driven by the adoption of AI.
- Prompt Engineers and Model Trainers: As generative AI tools are embedded into workflows, companies need specialists who can fine-tune models, craft effective prompts, and train tools on proprietary datasets.
- AI Literacy Trainers and Change Champions: Technology alone doesn't transform an organization—people do. These roles help reskill teams, drive adoption, and ensure AI tools deliver value.
For midmarket IT leaders, these roles open the door to newopportunities for innovation, efficiency, and growth in the AI era.
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Why This Matters for the Midmarket
Unlike large enterprises, most midmarket companies don't have the luxury of complete AI centers of excellence or in-house R&D labs. But they do have the opportunity to be agile if they make the right workforce decisions.
Unfortunately, too many midmarket leaders assume AI is strictly a technology investment. It's not. It's a workforce transformation and business modernization initiative. Failing to align talent with technology means digital initiatives stall, platforms go underutilized, and ROI evaporates.
According to Gartner, many mid-size enterprises risk failing to operationalize their AI strategies without stronger AI-leadership and talent capabilities.
Silver Tree Use Case
A midmarket manufacturer exploring AI-driven performance analytics may lack the internal resources to connect diverse data sources, configure AI models, and embed insights into day-to-day operations. In scenarios such as this, Silver Tree has been able to quickly assemble a tailored team, including an AI integration lead, a data quality analyst, and an Organizational Change Management (OCM) specialist, to help companies implement AI-enabled analytics, ensure data quality, and prepare employees to adopt new workflows.
By using a hybrid team model that combines onshore and offshore resources, clients have achieved up to 40% cost savings compared to onboarding full-time employees. Additionally, as client needs evolve, Silver Tree adapts team composition to align with shifting priorities and ensure continued value.
What to Do Now: Building an AI-Ready Workforce
To avoid these pitfalls, midmarket IT and business leaders must:
- Audit their existing workforce to identify roles at risk and emerging needs
- Reskill and redeploy talent to align with automation and AI capabilities
- Supplement with external expertise, such as AI integration teams/pods or advisory support
- Create a governance structure to ensure responsible and strategic use of AI
AI won't replace your team, but your team must evolve to work alongside AI. The sooner companies take proactive measures, the better their outcomes.
Is Your Workforce Ready for AI?
Don't assume your existing team is fully prepared to unlock AI's value. Download our AI-Ready Workforce Checklist to assess your organization's readiness and contact Silver Tree to arrange a Workforce Assessment.
Amanda spent the early years of her career working for large, professional service companies, such as Accenture, Deloitte, and KPMG. Midway through her career, she realized her expertise would make more of an impact if focused on smaller, high-growth tech companies, where her leadership and marketing strategy have positively impacted their success and bottom line.
During her tenure at KPMG, Amanda played a pivotal role in launching one of the company’s global service lines and its Global Valuation Institute. Her marketing expertise has since been instrumental in growing sales pipelines, shortening sales cycles, and increasing revenue, significantly altering the business trajectory of small and mid-size companies. Amanda earned her degrees in Marketing—B.S. from DePaul and M.B.A. from Northern Illinois University. In 2021, Amanda received her certification in Digital Marketing from Northwestern’s Kellogg School of Business.
