How AI in ERP and EPM Systems is Transforming Business Intelligence
By Finance, Uncategorized

Most businesses already have ERP. It’s a staple that supports finance functions of all sizes, managing transactional workflows, and maintaining operational continuity. But traditional ERP wasn’t built to answer the questions today’s finance leaders need to ask. Despite the EMP market being expected to reach USD 12.03 billion by 2032, too few business are unlocking the strategic benefits of EPM sitting on top of their ERP system. The answer? Embedding AI in ERP systems to turn static data into dynamic, predictive intelligence. AI-powered systems provide context around data and foresight, giving CFOs the ability not just report on what happened, but model what comes next and act accordingly.

And yet, despite this potential, many organisations remain stuck. Legacy mindsets, fragmented systems, and underinvestment in AI-driven EPM tools mean that finance functions remain reactive, focused on past performance, not future opportunity.

So, what’s really holding your business back from transforming business intelligence?

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The Strategic Role of AI in ERP and EPM

In today’s volatile economy, the ability to accurately anticipate risk, model outcomes, and optimise costs makes all the difference. Using AI in ERP systems offers a direct path to competitive advantage. But using it properly means understanding the AI tools you choose and how they can be applied successfully across performance management.

As such, organisations are always looking for new ways to create value through the application of technology. The real opportunity in AI-integrated ERP and EPM platforms lies in their strategic application.

AI-integrated ERP and EPM platforms enable organisations to:

  • Turn fragmented, backwards-looking data into forward-looking insight
  • Model multiple business scenarios in real time
  • Optimise resource allocation through predictive analytics and anomaly detection

This means ERP and EPM can now serve as the analytical foundation for capital planning, risk mitigation, and strategic forecasting. Unsurprisingly, the value that AI in ERP and EPM systems can create means organisations are acting.  58% of CFOs are now investing in AI and advanced analytics, according to PwC. The intent is there. But many organisations are experiencing challenges when unlocking it.

Let’s explore what those challenges look like and what you can do to overcome them:

 

Enhancing Decision-Making Through Predictive Intelligence

Many businesses rely on static models and backwards-looking data to drive financial planning cycles. AI transforms this model through continuous learning algorithms that adapt as new data flows in. This dynamic modelling enables finance leaders to:

  • Stress-test strategies under multiple economic scenarios
  • Anticipate working capital constraints before they hit
  • Identify margin erosion across SKUs or regions in real-time

In practical terms, integrating AI in ERP improves decision quality, and it improves decision velocity. In markets where agility is often the differentiator, this matters.

 

Real-Time Reporting and the Elimination of Latency

Traditional ERP systems often suffer from latency and siloed data sets. AI-enhanced ERP platforms are transforming monthly closes into continuous reporting, liberating finance teams from manual reconciliations and spreadsheet sprawl. AI resolves this by enabling real-time data harmonisation across functions. That means:

  • CFOs receive live dashboards with KPI updates
  • Finance teams operate from a single source of truth
  • Stakeholders gain immediate visibility into P&L shifts

For organisations operating in high-stakes or high-volume environments, the impact on governance and investor confidence is substantial.

 

Cost Reduction and Performance Optimisation

Yes, embedding AI in ERP and ERM systems automates routine accounting tasks. But focusing on automation alone is reductive. The broader opportunity lies in performance optimisation. Access to AI tools and advanced analytics allows finance teams to move beyond cost containment and towards driving strategic outcomes. That might be through better pricing models, more precise budgeting, or improved capital efficiency.

Other examples include:

  • Using AI to optimise procurement decisions based on forecasted demand
  • Enhancing FP&A with machine learning to identify cost anomalies across business units
  • Redesigning working capital models with predictive payment behaviour

 

New Leadership Capabilities and Skillsets

Technology alone will not drive value. It is the leadership capacity around it that determines success. As ERP and EPM systems evolve, so too must the leaders guiding their deployment. Modern finance leaders require a skillset that spans finance, technology, strategy, and people management. Critically, this isn’t about developing new skills in isolation. It’s about reframing the role of finance as a value enabler, underpinned by technology.

Increasingly, firms are augmenting their leadership teams with subject matter experts, consultants, and project-based contractors to accelerate delivery and inject external capability.

Look for professionals with:

  • Commercial Insight
    An ability to connect AI-enabled data points to real-world business levers, interpreting beyond the numbers to guide investment, expansion, or restructuring decisions.
  • Digital Confidence
    Leaders must understand the mechanics of AI-driven systems well enough to challenge assumptions, guide implementations, and spot limitations in vendor solutions.
  • Change Leadership
    ERP transformation is not only about technology. It demands behavioural and cultural change. Leaders must inspire trust, secure buy-in, and lead through ambiguity.
  • Cross-Functional Influence
    Modern finance leaders must collaborate with IT, operations, procurement, and HR to ensure ERP data is integrated and acted upon enterprise-wide.
  • Ethical and Regulatory Awareness
    As AI becomes more embedded, leaders must navigate its ethical implications, including bias, transparency, and compliance risks, while continuing to ensure robust governance.

 

What Smart Hiring Looks Like in an AI-Driven ERP Environment

Because success hinges on hiring individuals who understand the implications of AI in ERP and ERM systems, and who can shape the organisation around it, organisations require a more considered, consultative approach to hiring.

Smart hiring doesn’t mean defaulting to permanent recruitment. It means leveraging a blend of permanent, interim, contract, and consultancy solutions to source professionals who can elevate internal capability, close skill gaps, and drive faster impact.

These qualities are harder to spot on a CV. Which is why your recruitment partner must know what to look for, and where to find it.

Key hiring strategies include:

  • Interim Transformation Leadership
    Hiring interim Programme Directors or Finance Transformation Leads with experience in AI-enabled ERP rollouts provides a fast route to stabilisation, continuity, and momentum during critical phases.
  • Strategic Workforce Planning
    Building internal ERP capability isn’t a one-off hire. It requires mapping out future skill requirements across finance, IT, and data functions and ensuring your workforce is fit for purpose over a 3–5-year horizon.
  • Capability Over Credentials
    Focus hiring on functional impact and behavioural competencies, not just past employers or system names. Candidates who have led through ambiguity, built coalitions, or course-corrected challenged implementations are worth their weight in gold.
  • Hybrid Talent Models
    Use a blend of permanent and interim talent to meet variable demands. Interim finance leaders bring specialist capability on-demand. Permanent hires ensure continuity and institutional knowledge post-transformation.
  • Cultural Fit and Communication Skills
    AI-enabled transformations rise or fall on communication. Leaders must explain the why behind the tech, demystify the data, and lead human-centric adoption across teams.

At Cedar, we partner with clients to build AI-ready finance functions. That means:

  • Access to senior finance professionals with hands-on ERP and EPM transformation experience
  • Contract and interim talent to plug critical gaps or accelerate delivery
  • Project-based SoW teams tailored to your milestones and budget
  • Real insight into the talent landscape. Who’s delivering, who’s available, and who’s adding value
  • Access to ERP subject matter experts to bridge theory and implementation

If you’re planning an ERP transformation, reassessing your EPM capability, or looking to inject AI literacy into your finance team, we can help.

Contact us today to discuss how Cedar can support your finance recruitment strategy in an AI-driven environment.