Internal Audit Priorities for 2026: The Critical Focus Areas Audit Leaders Must Address
PUBLISHED
January 20, 2026
By Tom McLeod, Senior Advisor, Internal Audit & AI | Former Chief Audit Executive and Chief Risk Officer
This is my perspective on what will matter most to Internal Audit in 2026, arguably the most important year in the profession’s history.
The foundations of the profession still matter, but the environment has profoundly changed: AI-enabled processes, real-time decisioning and constant organisational change are raising expectations for assurance that is current, clear and defensible.
This piece is my perspective - grounded in decades as a Chief Audit Executive and Chief Risk Officer and informed by what I’ve seen globally in audit functions across industries and jurisdictions over the past year.
It’s designed as a practical blueprint: the priorities I believe will define high-performing teams, and the moves that create momentum quickly.
My hope is that this helps you aim higher.
In 2026, Internal Audit must choose not simply to keep pace with change, but to lead it - building real-time, evidence-driven assurance that strengthens trust, sharpens decisions, and makes organisational resilience unmistakable.
“The greatest danger in times of turbulence is not the turbulence; it is to act with yesterday’s logic.” Peter Druker
Internal Audit is currently experiencing the most consequential transformation in its history.
For decades, the profession has refined the craft of risk-based planning, sampling, walkthroughs, and point-in-time reviews. Those foundations will remain valuable - but they are no longer sufficient.
The speed and complexity of modern organisations, coupled with the rise of AI-driven processes and real-time data flows, is forcing Internal Audit functions to adapt.
Risk profiles now mutate in hours, not quarters.
Boards and Management are demanding assurance immediacy.
Regulators are shifting to dynamic oversight.
Across every geography and every industry, Internal Audit teams are confronting the same reality: the traditional model cannot keep pace with the way modern systems operate.
Why 2026 is a defining year for Internal Audit
As we enter 2026, this gap between legacy audit models and modern organisational dynamics is impossible to ignore.
The coming year will not reward incremental adjustments or localised pilots.
2026 will reward audit functions that reshape their priorities, redesign their operating protocols, and rebuild their capabilities around intelligent evidence, continuous monitoring, and adaptive risk coverage.
This is why 2026 must be defined by a clear, deliberate set of focus areas.
Over the past year, I’ve spoken with Chief Audit Executives (CAEs) across industries, across countries and, reviewed dozens of audit functions, and watched how quickly expectations are shifting.
What’s clear is that Internal Audit can no longer rely on the rhythms and assumptions that carried us through the last decades.
The priorities below come directly from what I’m seeing inside high-performing teams and from the pressure points emerging within their organisations.
These are the eight focus areas I believe audit leaders must elevate now - if they want their functions to stay credible, fast, and trusted in a landscape being reshaped by forces we’ve never had to navigate before.
1: Regulatory acceleration will reshape audit focus
When I’ve advised regulators, the message has been blunt: if you keep running supervision like a scheduled inspection, firms will keep optimising for the meeting not for real-world performance. In one engagement, we shifted the approach from “send us your annual pack” to “show us what you’re seeing this week”: we asked for simple, current proof that key obligations were being met (what changed, what broke, how fast it was fixed, and who signed off), and we made it clear that new guidance would be treated as “live” rather than something to park for the next cycle.
My advice was to create a steady rhythm of small, frequent check-ins, keep a clear record of regulatory updates and what they mean in practice, and align with Internal Audit and compliance so organisations build habits of staying current - not scrambling when a letter arrives.
Regulators worldwide are shifting from periodic to dynamic oversight.
This is evident in sustainability disclosures, cyber-resilience frameworks, financial controls modernisation, and the rapid emergence of AI governance.
In 2026, Internal Audit needs to treat regulatory acceleration as a permanent condition, not a temporary aberration.
Key priorities include:
- Establishing real-time monitoring of regulatory updates across all relevant jurisdictions, using automation that flags changes, maps them to affected controls, and maintains a defensible audit trail.
- Partnering with compliance functions to test controls continuously, especially in areas where regulators are shifting toward outcomes-based supervision and expect near-instant evidence of effectiveness.
- Using data-driven tools that align to global standards - ISO 27001, ISO 42001, NIST, COSO - ensuring Internal Audit can demonstrate clear linkage between regulatory obligations, control design, operational evidence, and assurance conclusions.
The strongest Internal Audit teams will become interpreters and integrators of regulatory change, not late responders to it.
2: Unstructured data mastery
Internal Audit’s perpetual evidence challenge is unstructured data: PDFs, scanned invoices, multi-page contracts, emails, reconciliations, extracts, certifications. High-performing teams in 2026 will treat unstructured data competency as a baseline skill.
Capabilities required include:
- Extracting reliable data from inconsistent documents
- Detecting anomalies, missing pages, or altered materials
- Converting messy evidence into structured audit artefacts
- Enabling automated testing and real-time monitoring
This is the capability most Internal Audit teams underestimate.
The Chief Audit Executive of a global lending team recently approached me at a conference and mentioned that they were spending weeks reconciling multi-page loan documentation. By automating unstructured document extraction across thousands of files, they reduced manual review by over 80% and modernised their audit file into a structured, traceable evidence model. It immediately elevated both speed and assurance quality.
A consumer goods audit function faced a similar challenge with vendor agreements. These contracts varied in layout, structure, and terminology. Once they adopted unstructured-data tooling, the team could extract comparable fields across documents, perform automated exceptions testing, and unify their contract analysis workflow. The uplift was not only in efficiency, but in accuracy and consistency.
3: Evidence traceability will define audit credibility
In 2026, the credibility of assurance will be defined by the traceability of evidence.
Boards and Management are asking sharper questions about:
- How findings were validated
- Whether evidence is digital, complete, and reproducible
- How data was collected and governed
Internal Audit must invest in 2026 in:
- Artificial Intelligence and Automation
- Transparent documentation workflows
- Systems that allow reviewers to reconstruct exactly what the auditor saw
Strong Internal Audit functions in 2026 will treat evidence quality as a core competency, not a technicality.
Audit credibility now depends on the ability to prove how every conclusion was reached, including the data lineage, extraction process, and linkage to source materials.
This requires capability in:
- Tracing values from source to extraction to test step to conclusion
- Demonstrating reproducibility under regulatory or other stakeholder scrutiny
- Validating completeness and detecting missing evidence
- Documenting where automation contributed and where judgement was applied
In conversations with CAEs this year, one of the most consistent concerns has been: “Can we defend our evidence trail?”
One global insurer I spoke with recently realised that their audit conclusions were defensible, but their documentation was not.
By redesigning their evidence workflow to include extraction-level traceability, they created a transparent chain from source document to final conclusion - transforming their function’s credibility with their key stakeholders.
A major financial services audit team similarly discovered during a quality review that they could not reliably reproduce key calculations that formed the basis of their independent assurance.
Once the team implemented a structured extraction and linkage approach they were able to re-run testing steps with full visibility over the evidence lineage.
This reproducibility became their strongest credibility signal.
For many years IIA quality assessment reviews continue to identify deficiencies in evidence traceability as a root cause of audit-file rework. Teams simply cannot defend conclusions if the underlying evidence chain is unclear.
4: Intelligent automation and AI Agents
By 2026, automation will no longer be something Internal Audit experiments with on the side. It will sit at the core of how audit work is designed, executed, and reviewed.
The most effective audit functions are already moving beyond isolated automation use cases and embedding intelligent automation directly into their methodology. In practice, this means redesigning how audit work is structured so automation is part of the workflow rather than an afterthought.
High-performing teams are embedding automation across:
- Workpapers designed to support automated testing
- Standardised documentation and review processes
- Evidence capture that is digital, structured, and traceable
- Direct linkage between source data, testing steps, and conclusions
When done well, intelligent automation delivers more than efficiency. It:
- Reduces manual effort without increasing complexity
- Improves consistency across testing and documentation
- Strengthens traceability from source evidence to conclusion
- Eliminates rework during review
- Converts evidence into insight faster than traditional methods
I recently spoke with a global manufacturer that embedded automation into its standard audit workpapers by enabling direct linking between source documents and testing procedures. This single change eliminated hundreds of hours of manual tie-backs and significantly improved review quality. Reviewers could immediately see where evidence originated, how it was extracted, and whether the logic applied was appropriate. The outcome was not just efficiency, but confidence.
This foundation is what enables the next stage of automation maturity:
Agentic Automation
Agentic AI introduces systems capable of performing multi-step actions across audit workflows. By 2026, these capabilities will increasingly support Internal Audit teams, particularly in environments dealing with high volumes of transactions, contracts, or unstructured evidence.
Common agent-supported activities include:
- Classifying and organising large volumes of documents
- Extracting key fields from unstructured evidence
- Creating structured linkages across the audit file
- Preparing preliminary testing outputs for review
This shift does not reduce the role of auditors.
It changes it.
The strongest audit teams treat audit agents as they would a junior team member: fast, scalable, and highly capable, but always subject to review and challenge.
Auditors remain responsible for reviewing AI-generated outputs, challenging assumptions and classifications, overriding conclusions when context is misunderstood, and documenting where human judgement intervened. Supervision, not blind trust, becomes the defining skill.
I recently advised a global retail audit group deploying an AI agent to pre-process thousands of purchasing documents. The agent classified documents, extracted key fields, and created structured linkages across the audit file. Auditors then focused their time on reviewing anomalies, validating logic, and documenting their oversight. The time saved was significant, but the real gain was transparency. Every automated step was visible, reviewable, and defensible.
Automation is no longer a technical enhancement.
It is becoming the operating system of modern audit. Audit functions that embed intelligent automation and audit agents thoughtfully, with humans firmly in control, will unlock speed, scale, and insight that were simply not possible in the pre-automation audit model.
5: AI governance and transparent methods will define audit independence
My own journey into AI-enabled auditing started the same way it has for many CAEs I speak with: curiosity mixed with frustration.
I’d spent years watching talented auditors lose hours to document trawling, sampling debates, and evidence wrangling. The first time I ran an AI tool over a full (albeit small by what is now possible) population and it surfaced patterns I had never seen, it was obvious the profession was about to change fast.
That moment of possibility is familiar to many audit leaders. But as AI and automation move from experimentation into daily audit execution, the focus quickly shifts from what is possible to what is defensible.
As intelligent automation and audit agents become embedded in Internal Audit workflows, independence will be judged less by reporting lines and more by transparency of methods.
In 2026, stakeholders will ask sharper questions about how assurance conclusions are formed, particularly where AI and automation are involved.
These questions increasingly include:
- What tools were used, and why
- How automated outputs were validated
- Where human judgement intervened
- What assumptions or biases may exist
- Whether conclusions can be reproduced and defended
I’ve seen this play out repeatedly in conversations with CAEs. Audit Committees are no longer satisfied with knowing that automation was used. They want to understand how it was supervised, where judgement was applied, and whether conclusions can be reconstructed under challenge.
Internal Audit must build transparency directly into its methodology, not treat it as a compliance afterthought.
This includes:
- Clear documentation of automation and AI tools used
- Defined validation routines for AI-supported work
- Explicit records of human oversight and intervention
- Documented limitations and risk acceptance decisions
One global audit function I spoke with recently realised that while their conclusions were sound, they could not clearly explain how automated steps contributed to those conclusions. The issue was not the use of AI itself, but the lack of visibility into where automation ended and judgement began. That gap quickly became an independence concern.
In an AI-enabled audit environment, independence depends on the ability to reconstruct the path from source evidence to conclusion, including where automation contributed and where judgement was applied.
The strongest audit functions will not treat AI governance as a technical or regulatory exercise. They will treat it as a credibility requirement.
In 2026, independence will belong to the audit teams who can clearly explain their methods, defend their conclusions without ambiguity, and demonstrate control over both human and automated contributions to the audit process.
6: Replace the traditional audit universe with dynamic focus areas
The “audit universe” as we’ve defined it for decades is becoming obsolete, and I’ve heard that directly in conversations with CAEs who admit their plans are out of date before they reach the Audit Committee. A static inventory simply can’t keep pace with the fluidity, speed, and interconnectedness of modern operations let alone one fueled by AI.
In 2026, Internal Audit leaders should shift to dynamic focus areas, which evolve continuously and prioritise:
- Areas of high change velocity
- Risks with rapid escalation potential
- Processes with high dependency or complexity
- Controls affected by automation or AI
- Domains where stakeholders demand insight
Coverage will refresh frequently. Priorities will shift as new signals emerge. And Internal Audit will gain a clearer view of where attention truly matters.
This is not just a planning shift - it is a mindset shift toward adaptive assurance.
7: Internal Audit becomes a strategic builder of organisational trust
In a recent board session that I was privy to, the Chief Audit Executive interrupted the familiar “we’re a trusted brand” narrative and replaced it with a tight, real-time evidence pack - showing to the Audit Committee for the first time which key controls were performing this week, where exceptions were emerging and what had been fixed within days.
In the past, trust was mostly inferred from brand reputation, disclosure, and polished narratives.
In 2026, it shifts to something organisations must prove through real-time evidence, transparent AI behaviour, and consistent control performance. That makes trust a dynamic, data-driven differentiator rather than a static reputational asset.
Internal Audit should position itself as one of the primary trust-builders through:
- Independent validation
- Transparent evidence flows
- Continuous monitoring
- Clear reporting on key metrics
Boards are likely to increasingly use Internal Audit insights in:
- Investor communications
- Sustainability and ESG disclosures
- Strategic decision-making
- Reputation-management efforts
When Internal Audit builds trust through evidence and transparency, it becomes more than a control function - it becomes a strategic voice in how the organisation earns legitimacy.
8: New skills will define high performing audit teams
As intelligent automation and audit agents become embedded in audit methodology, the differentiator for Internal Audit is no longer access to technology. It is the skills of the people supervising it.
2026 is the year Internal Audit leaders must confront a simple reality: skills must evolve as quickly as risks do.
I’ve seen this shift up close.
When I first entered the profession, we celebrated sampling 40 invoices as if it were sophistication. Today, teams can interrogate millions of transactions in minutes, surface anomalies we never knew existed, and validate control behaviour in near real time.
High-performing audit functions now build teams with blended expertise across:
- Data interrogation and pattern recognition
- Analytics interpretation
- AI model validation and assurance
- Governance, behavioural and cultural risk
- Core process, cyber, and operational domains
And crucially, the best teams understand the emerging reality: AI and AI agents are not here to take over Internal Audit - they’re here to multiply its capability. The real differentiator is how well humans and machines work together.
This is not about turning auditors into data scientists. It is about equipping them to:
- Question data quality and lineage
- Understand and leverage - not fear - the limitations of AI
- Assess and monitor automated processes running at machine speed
- Challenge algorithmic behaviour with professional scepticism
- Use automation to eliminate low-value effort so auditors can focus on judgement, insight, and foresight
New roles will emerge, but the most important investment in 2026 is upskilling current staff so they can operate confidently in a changed world.
The blueprint for Internal Audit success in 2026
2026 is not just another audit year.
It is the year Internal Audit shifts decisively into a role defined by:
- Continuous assurance
- Intelligent analytics
- Transparent governance
- Hybrid human-AI teamwork
- Evidence-driven credibility
- Dynamic risk prioritisation
- Strategic communication
These focus areas provide a blueprint for that transition.
Internal Audit teams who prioritise them will operate faster, build deeper trust, and deliver stronger insights than ever before. Teams who defer transformation risk falling behind - not because they lack skill, but because they lack alignment with how modern organisations now operate.
My conclusion is clear: 2026 will favour audit teams that evolve with purpose, and the blueprint that follows shows exactly how to make that evolution real.
Where to start in 2026: Three practical moves for CAEs
The four actions below are not additional priorities. They are foundational moves that activate the blueprint above and create momentum across the ten focus areas.
1: Build a real-time evidence approach
Deploy continuous monitoring and evidence-capture capabilities for two high-velocity processes.
This immediately improves traceability, documentation quality, and assurance speed. It also lays the foundation for continuous assurance, regulatory responsiveness, and defensible audit conclusions.
2: Replace the annual plan with a living plan
Move from a static annual audit plan to a monthly refreshed plan driven by live risk signals and business-change data, and make the shift explicit to the Audit Committee.
This enables dynamic risk prioritisation and aligns Internal Audit with the operating rhythm of the business.
3: Set a minimum standard for AI use and oversight
This includes clear documentation of automation used, validation routines auditors can trust, explicit records of human judgement, and defined rules for when professional judgement must override automated outputs. This standard underpins audit independence, transparency, and confidence in AI-supported assurance.
From everything I’ve seen inside audit functions this year - across industries, jurisdictions, and maturity levels - the teams that lean into these shifts first are already pulling ahead in credibility, relevance, and influence.
I’m convinced that 2026 will be the year Internal Audit finally steps into a faster, more evidence-driven, and more strategic role, and this blueprint reflects the direction I believe the profession must take to get there.
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