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Let me paint a picture you’ll probably recognize.
Your IT team is talented. They’re dedicated. They work long hours. But when you ask what they’ve been working on, the answer is always some variation of “keeping the lights on.”
Meanwhile, your competitors are launching AI-powered features. They’re automating processes that your team still handles manually. They’re delivering new capabilities in weeks that would take your organization months.
What’s going on?
The answer, according to new research from Ensono surveying 500 IT leaders across the US and UK, is both simple and sobering: 75% of IT teams spend the majority of their time either maintaining day-to-day operations (57%) or reducing technical debt (18%). Only 25% can focus primarily on innovation.
After decades of architecting enterprise technology solutions and guiding organizations through digital transformation, I can tell you this isn’t a personnel problem or even a budgeting problem. It’s a legacy systems problem. And it’s getting worse.
The Hidden Tax of Legacy Infrastructure
Here’s a number that should alarm every business leader: nearly half (49%) of organizations spent more than budgeted on legacy system maintenance last year.
Think about what that means. Organizations planning maintenance costs with historical data, vendor relationships, and experienced teams still underestimated by enough that half exceeded their budgets.
This isn’t a rounding error. It’s a signal that legacy systems are fundamentally unpredictable and consuming resources faster than organizations can track.
I call this the “Legacy Tax,” the hidden, growing cost that diverts resources from strategic initiatives to keeping aging infrastructure functional. Like a tax, it compounds over time. Systems get older, expertise becomes scarcer, components reach end-of-life, integration with modern tools grows more complex.
And here’s the kicker: among IT teams spending most of their time on maintenance or debt reduction, 86% report that innovation is frequently delayed due to budget constraints.
Let me translate: the more time your team spends fighting fires, the less budget remains for preventing future fires. It’s a death spiral.
Why Risk Is Driving Modernization (And Why That’s a Problem)
When asked what’s driving their modernization efforts, nearly half of IT leaders (49%) cited the same factor: risk.
Specifically, risk from security vulnerabilities, loss of vendor support, or application downtime.
On the surface, this makes sense. Legacy systems present real, escalating risks:
- Unsupported software that no longer receives security patches becomes a playground for attackers
- Outdated architectures lack capabilities to integrate with modern security tools
- Aging hardware fails more frequently and takes longer to repair or replace
- Scarce expertise means fewer people who can respond when something breaks
- Compliance gaps emerge as regulatory frameworks evolve beyond legacy capabilities
From a cybersecurity perspective (a domain I’ve worked in extensively), legacy infrastructure is terrifying. You’re essentially trying to defend castles built before anyone imagined modern weapons.
But here’s the problem with risk-driven modernization: it’s reactive, not strategic.
When you modernize primarily to mitigate risk, you’re playing defense. You’re trying to prevent bad outcomes rather than enable good ones. This defensive posture often leads to:
- Minimum viable investments that address immediate threats without transforming capabilities
- Piecemeal approaches that reduce specific risks but don’t improve overall architecture
- Short-term thinking that trades one set of challenges for another
- Missed opportunities to leverage modernization for competitive advantage
Compare this to the 21% of organizations the research identifies as “ahead of the curve,” those using modernization proactively for competitive advantage. These organizations approach modernization strategically, asking not just “what risks can we eliminate?” but “what capabilities can we enable?”
The difference in outcomes is profound.
The AI Elephant in the Room
Let’s talk about artificial intelligence for a moment.
Every executive I speak with wants to know how AI can transform their business. They’ve read about AI-powered customer service, AI-driven analytics, AI-automated operations. They see competitors launching AI capabilities and feel pressure to keep pace.
Then they talk to their IT teams and discover a harsh reality: their infrastructure can’t support it.
The research confirms this. When asked about application modernization drivers, 42% of organizations cited “limited ability to adopt automation and AI” as a primary challenge.
Here’s why legacy systems and AI are fundamentally incompatible:
Data Access: AI models need data (lots of it, in consistent formats, accessible via APIs). Legacy systems often lock data behind proprietary formats, aging databases, and architectures predating API-first design.
Computational Resources: Training and running AI models requires significant computational resources. Legacy infrastructure typically can’t scale to accommodate these workloads efficiently.
Integration Complexity: AI services (whether cloud-based or on-premise) need to integrate with existing systems. Legacy architectures make this integration exponentially more complex.
Real-Time Requirements: Many AI use cases require real-time or near-real-time data processing. Legacy systems built for batch processing struggle to meet these requirements.
But here’s the fascinating insight from the research: among organizations furthest along in their modernization journey, 60% say AI has accelerated their modernization outcomes.
This creates a virtuous cycle: modernization enables AI adoption, which accelerates further modernization, which enables more sophisticated AI use cases.
The challenge is reaching that inflection point. For organizations stuck in maintenance mode with legacy systems, AI remains aspirational rather than actionable.
Wondering if your infrastructure can support AI? Take our free AI assessment or call us at 919-422-2607 to find out.
Why “Rip and Replace” Usually Fails
When executives recognize the legacy systems problem, the instinctive solution is often: “Let’s just replace everything with modern systems.”
I’ve seen this impulse countless times. And I’ve seen it fail almost as often.
The research validates this experience. Only 11% of organizations plan to fully retire legacy systems and migrate everything to alternative platforms. Meanwhile, 47% plan to modernize some applications while keeping core systems intact, and another 29% plan to modernize applications without migrating off legacy infrastructure.
Why the conservative approach? Because wholesale replacement ignores several realities:
Business Continuity: The systems you call “legacy” are often the systems running mission-critical operations. Replacing them risks disruption that most businesses can’t afford.
Hidden Dependencies: Legacy systems have dependencies (technical, procedural, organizational) that exceed what any documentation captures. Replacement projects routinely uncover surprises.
Cost and Timeline: Comprehensive replacement programs typically cost more and take longer than anticipated. The research shows 49% of organizations already exceed maintenance budgets. Imagine the overruns on replacement projects.
Organizational Capacity: Most organizations lack the bandwidth to execute large-scale replacement while maintaining current operations. Something has to give, and it’s usually the replacement initiative.
Sunk Investment: Legacy systems represent millions in investment and decades of accumulated business logic. Discarding that completely is often economically irrational.
This doesn’t mean resignation to legacy forever. It means embracing a more nuanced approach.
The Hybrid Path Forward
The most successful modernization strategies I’ve architected and implemented follow what I call the “Hybrid Path,” acknowledging that most organizations will operate in hybrid environments (legacy plus modern) for years, and optimizing for that reality.
The research supports this approach. Among organizations modernizing applications on legacy infrastructure, 54% are specifically focused on integrating legacy workloads with cloud and newer platforms.
This focus on integration over elimination reflects mature thinking. Instead of asking “how do we get rid of legacy?” it asks “how do we make legacy and modern systems work together effectively?”
Here’s what the Hybrid Path looks like in practice:
Phase 1: Assessment and Prioritization
Don’t modernize everything. Modernize strategically.
Map your application portfolio. Identify which applications:
- Directly impact revenue or customer experience
- Block adoption of critical capabilities (especially AI/automation)
- Present the highest security or compliance risks
- Offer the clearest ROI from modernization
Prioritize these for early modernization while maintaining systems that work adequately.
Phase 2: Selective Migration
Move your highest-priority applications to modern platforms using the approach that fits their characteristics:
- Rehosting (lift-and-shift) for applications where cloud infrastructure provides immediate value
- Replatforming for applications benefiting from managed services and containerization
- Refactoring for applications where architecture limits capabilities
- Replacing where commercial alternatives provide better value
- Retaining core systems temporarily while modernizing around them
The research shows 52% of organizations find refactoring applications to be their biggest challenge during migration. This is where architecture expertise and proven patterns become essential. Don’t wing it.
Phase 3: Build the Bridges
Here’s where many organizations stumble: they modernize some applications but fail to create robust integration between legacy and modern systems.
The 38% of IT leaders identifying “stronger hybrid IT management tools” as their top modernization accelerator have recognized this gap.
Invest in:
- API layers exposing legacy system data and functionality
- Integration platforms managing data flows between systems
- Unified monitoring providing visibility across the stack
- Consistent security controls spanning hybrid environments
- Centralized data strategies enabling analytics across systems
These integrations are not temporary band-aids. They’re the foundation enabling you to operate effectively in hybrid mode while progressively modernizing remaining workloads.
Phase 4: Continuous Optimization
Modernization isn’t a project. It’s a practice.
Establish metrics tracking:
- Percentage of IT time spent on innovation versus maintenance
- Cost trends for legacy versus modern systems
- Performance improvements from modernized applications
- Business outcomes (time-to-market, customer satisfaction, revenue impact)
Use these metrics to inform ongoing decisions about priorities and resource allocation. The organizations ahead of the curve have 72% likelihood of having highly structured measurement approaches compared to just 23% of those playing catch-up.
The Talent Challenge Nobody Wants to Talk About
Here’s an uncomfortable truth: 90% of organizations report at least one talent gap hindering their modernization efforts.
The most common gaps:
- Cloud architecture and migration expertise (27%)
- Application modernization skills (19%)
- Cybersecurity expertise (14%)
This creates a classic chicken-and-egg problem. You need these skills to modernize. But you’re spending 75% of your IT resources on maintenance, leaving little capacity to develop new capabilities or attract talent with modern skills.
The data shows 95% of organizations are working with third-party partners (cloud providers at 58%, technology vendors at 53%, and IT consultants at 49%) to address these gaps.
But partnerships alone aren’t sufficient. The organizations furthest ahead in modernization are significantly more likely to work with IT strategy consultants (54% versus 35% of those behind), suggesting that strategic guidance (not just execution support) accelerates outcomes.
My recommendation: approach partnerships with explicit knowledge transfer goals. Don’t just outsource modernization. Use external expertise to develop internal capabilities. Otherwise, you’re trading one dependency (legacy systems) for another (vendor relationships).
What AI Can and Can’t Do for Modernization
Given my frequent media appearances discussing AI, I’m often asked: “Can AI help with modernization itself?”
The short answer is: yes, but with significant caveats.
The research reveals mixed experiences with AI’s impact on modernization:
- 39% say AI tools have accelerated efforts
- 33% say AI introduced new challenges
- 23% report mixed impact
What explains these varied outcomes?
AI works best as an accelerator, not a substitute. Organizations furthest along in modernization see the most benefit from AI (60% report acceleration). Organizations earlier in the journey often find AI adds complexity.
Here’s why: AI can accelerate well-defined, well-understood processes. But modernization often involves discovering undocumented dependencies, making architectural decisions with incomplete information, and navigating organizational change. These require human judgment and expertise.
Where AI helps:
- Code analysis identifying dependencies and potential issues
- Migration planning assessing complexity and effort
- Testing automation validating migrated applications
- Documentation generation capturing system knowledge
- Pattern recognition identifying similar challenges and solutions
Where AI struggles:
- Strategic decision-making about which systems to modernize when
- Organizational change management helping teams adapt
- Custom integration development between dissimilar systems
- Exception handling when migrations encounter unexpected issues
The 23% of managers reporting AI acceleration compared to 49% of C-suite leaders suggests a gap between leadership optimism and implementation reality. Those closest to the work face challenges that executives may not fully appreciate.
The Security Dimension: Don’t Create New Vulnerabilities
As someone who frequently speaks about cybersecurity, I need to emphasize something critical: modernization done poorly can make security worse, not better.
Hybrid environments create new attack surfaces:
- Integration points between legacy and modern systems
- Inconsistent security controls across platforms
- Visibility gaps where security teams can’t monitor activity
- Complex identity and access management across diverse systems
- Compliance challenges spanning different architectural paradigms
The 35% of organizations citing “hybrid IT complexity” as a top modernization challenge are grappling with this reality.
October is Cybersecurity Awareness Month, making this particularly timely. Organizations must approach modernization with security-first principles:
Zero Trust Architecture: Don’t assume trust based on network location. Verify every access request regardless of origin.
Unified Security Operations: Deploy tools providing consistent visibility and control across hybrid environments.
Security by Design: Incorporate security requirements into modernization planning from day one, not as afterthoughts.
Automated Compliance: Build compliance monitoring into modernized systems rather than treating it as separate.
Incident Response Planning: Update playbooks to address hybrid environment scenarios before incidents occur.
The 14% of organizations citing cybersecurity talent gaps should prioritize security partnerships and managed security services to avoid creating vulnerabilities during transition periods.
Five Things You Can Do Tomorrow
After reading about all these challenges, you might feel overwhelmed. Where do you even start?
Here are five concrete actions you can take immediately:
1. Calculate Your Legacy Tax
Sit down with your CFO and IT leaders. Calculate:
- Total annual spend on legacy system maintenance
- Percentage of IT team time spent on maintenance versus innovation
- Cost overruns from legacy systems in the past 3 years
- Revenue opportunities delayed due to legacy constraints
Present this to your leadership team not as an IT problem but as a strategic business constraint.
2. Identify Your Blocking Applications
Which specific applications are preventing you from:
- Launching AI-powered capabilities?
- Implementing automation that could reduce costs?
- Delivering customer experiences that differentiate you?
- Integrating with modern platforms and partners?
Make a list. Prioritize it by business impact. These are your modernization priorities.
3. Assess Your Measurement Maturity
Can you answer these questions with data?
- What percentage of IT effort goes to maintenance versus innovation?
- How long does it take to deploy new features?
- What’s the total cost of ownership for key applications?
- How do performance metrics trend over time?
If you can’t answer these, implementing measurement disciplines is your first modernization priority.
4. Audit Your Partner Relationships
For each technology partner, ask:
- Are they helping us build internal capabilities or creating dependencies?
- Do we have clear metrics defining successful engagement?
- Are we gaining strategic guidance or just execution support?
- Could we sustain modernization momentum if the partnership ended?
If you’re uncomfortable with the answers, restructure partnerships to emphasize knowledge transfer.
5. Create an Innovation Budget
Even if small, establish a dedicated budget that cannot be consumed by maintenance. Ring-fence resources for forward-looking initiatives. Start at 10% to 15% of IT spending if you need to, but protect it fiercely.
Among organizations keeping pace or ahead, this dedicated innovation capacity is common. Among those falling behind, it’s typically absent.
Need help getting started? Request your free AI assessment or call 919-422-2607 to speak with our team.
The Window Is Closing
Let me be direct: the gap between organizations leading in modernization and those falling behind is widening rapidly.
The 21% ahead of the curve aren’t just maintaining systems better. They’re:
- Accelerating product development through modern architectures
- Redirecting resources from maintenance to innovation
- Delivering superior customer experiences through modern applications
- Leveraging AI and automation to compound advantages
Meanwhile, organizations stuck in maintenance mode face:
- Rising costs consuming innovation budgets
- Escalating security risks from aging infrastructure
- Limited ability to capitalize on AI opportunities
- Competitive pressure from more agile rivals
The window for catching up is narrowing. As leading organizations compound advantages through AI-accelerated development and modern architectures, the gap becomes increasingly difficult to close.
The Choice Is Yours
You have a choice to make, not whether to modernize (that ship has sailed), but how to modernize.
You can continue deferring modernization, hoping legacy systems persist indefinitely, until competitive pressure or catastrophic failure forces reactive, desperate action.
Or you can approach modernization strategically and deliberately, embracing hybrid realities, prioritizing based on business value, building internal capabilities, and leveraging external expertise thoughtfully.
The research shows both paths clearly. The 21% ahead of the curve versus the 4% struggling to keep up. The 60% seeing AI acceleration versus the 33% finding it introduces new challenges. The 72% with structured measurement versus the 49% with only somewhat structured approaches.
The difference isn’t luck or resources. It’s strategy, discipline, and leadership commitment.
Your IT team isn’t fighting fires because they’re incompetent or because you’re not investing enough. They’re fighting fires because they’re trapped in systems that consume resources faster than you can provide them.
The question isn’t whether to modernize. It’s whether to start now, when you can do it strategically, or later, when you’ll have no choice but to do it reactively.
Choose wisely. Your competitive position depends on it.
Ready to start your modernization journey? Get your free AI assessment today or call our experts at 919-422-2607. We’ll help you assess your current state, identify priorities, and develop a strategic roadmap that balances innovation with business continuity.
Craig Petronella is the Founder and CEO of Petronella.ai and Petronellatech.com, providing AI strategy, cybersecurity, and compliance solutions for enterprises. As a best-selling Amazon author and frequent media commentator on AI and cybersecurity trends, Craig helps organizations navigate digital transformation. Learn more at petronellatech.com.