AI in IT: How expectations are resetting for CIOs in healthcare

The healthcare IT demand for “more with less”

Healthcare IT organizations have always been asked to do more with less, but AI has changed the equation entirely. Across strategy, planning, deployment and operations, healthcare organizations now have access to tools that help dramatically accelerate work that once took months: 

• Strategies and business cases that previously required weeks of interviews, analysis and slide production can now be developed in weeks — not months. 
• ERP vendors are increasingly promoting a zero‑configuration mindset, using AI to standardize workflows and help reduce customization. 
• EHR vendors are following suit, using automation and intelligence to help streamline build, testing and optimization activities. 

The disruptive impact is clear: Healthcare IT delivery, whether performed by consultants or internal teams, is becoming faster, more standardized and more insight‑driven. 

AI doesn’t just make healthcare IT work faster. It fundamentally raises the bar for what “good” looks like. If strategy cycles can be compressed, if builds can be standardized and if testing can be automated, then the expectation cannot simply be lower cost. The expectation becomes: greater clarity, faster decision‑making, higher certainty and measurable outcomes, sooner. 

In other words, AI shifts value away from effort and toward judgment. 

This mirrors what appears to be happening in management consulting more broadly: AI automates much of the work traditionally performed by junior staff while elevating the importance of roles focused on problem framing, orchestration, interpretation and executive guidance.  

What this means for the HIT workforce

This shift applies directly to healthcare IT professionals, including EHR analysts, application teams, digital leaders and CIO organizations. AI will not automatically replace HIT talent, but it will differentiate them.  

The future belongs to individuals who know which AI tools are available and where they fit in the IT lifecycle. Those who use these tools effectively will understand how AI‑enabled insights translate into value for clinicians, patients, finance leaders and executives. 

For example, AI can now support:  

• Accelerated application configuration and testing  
• Rapid analysis of workflow variation
• Faster identification of technical debt and optimization opportunities  
• Synthetic test data creation for build validation
• More proactive system monitoring and incident prevention  

The winners will not be those who simply “do the work,” but those who can orchestrate AI to deliver outcomes. 

The rise of the AI solution architect

One role we see emerging rapidly in healthcare IT is what could be described as the AI solution architect. This individual sits at the intersection of:

• Technology
• Process
• Clinical and operational context
• AI‑enabled tooling 

Their value is not in writing code or manually configuring systems, but in designing AI‑assisted delivery models that help accelerate deployment, reduce risk and improve quality. 

Where partners still matter

If AI enables individuals and organizations to do more, when does it still make sense to involve a consulting partner? In our experience, there are several situations where partnership remains essential: 

• Complex transformations where AI can accelerate analysis but cannot replace deep domain judgment 
• High‑risk initiatives, such as large‑scale EHR or ERP transitions 
• Capacity gaps, where AI increases productivity but does not eliminate the need for experienced leadership 
• Change management, governance and stakeholder alignment — areas where human trust is still critically important 

The role of the consultant evolves from “extra hands” to strategic accelerator, aiming to bring expertise, structure and AI‑enabled delivery at speed. 

What CIOs and executives should expect now and into the future

For CIOs and executive leaders, this shift demands a reset in expectations:  

• Expect faster timelines, but also demand better clarity  
• Expect smaller teams, but higher quality insights  
• Expect AI‑supported delivery, not AI experimentation
• Expect partners and internal teams to explain how AI is being used 

This also has implications for RFPs and vendor selection. Health systems that fail to account for AI‑enabled delivery may risk paying for outdated models that no longer reflect how work gets done.

Two recommendations for the future

As healthcare organizations navigate this transition, we see two practical recommendations emerging: 

1. Redefine what “good” looks like for IT talent and partners. Move beyond role‑based expectations (“analyst,” “consultant,” “builder”) and focus instead on capability‑based outcomes: insight speed, decision quality and execution certainty. 
2. Invest in AI fluency, not just AI tools. The real differentiator will not be access to AI but the ability of leaders and teams to use it responsibly, effectively and in service of patient‑centered outcomes. 

Final thoughts on AI in IT

AI is not eliminating the need for healthcare IT professionals or consultants. But it is reducing the tolerance for slow, labor‑heavy, low‑insight delivery models.  

As AI continues to evolve, so too must our EHR and digital strategies. This is not a one‑time shift — it’s an ongoing recalibration of how technology can be deployed, optimized and aligned to enterprise goals.  

The question isn’t just “how do we do more with less?” It’s "what does ‘more’ actually look like in an AI‑enabled future?”  

For some, it will mean faster delivery. For others, it will mean better insights or more standardized operations. But for forward-thinking organizations, it will mean reimagining what is possible, from how systems are configured and maintained to how decisions are made and value is realized.  

Those who are willing to challenge legacy approaches, embrace the acceleration of progress and imagine new possibilities will not just keep up with change but define what comes next.