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Strategy and value management

� IA’s role in emerging topics such as ESG, cyber threats, and disruptive events (transactions, transformations, etc.)

� Broadening risk coverage as business model and digitization efforts evolve

� Integration and coordination across three lines of defense (e.g., common risk taxonomy, addressing the talent drain)

� Getting to the right Key Performance Indicators (KPIs) to measure value for the business 

Risks and responses

� Cybersecurity (e.g., ransomware incident response*, phishing, hacking, data theft)

� Business and operational resiliency (e.g., supply chain interruptions*)

� Third-party risk management

� Workforce* (e.g., contingent workforce, upskilling and reskilling talent, distributed tax implications)

� Regulatory compliance (e.g., more regulated environment, expanded role for IT)

� Mergers and acquisitions* (e.g., portfolio management, transformation of the organization)

� Digital transformation (e.g., ERP, continuous control monitoring)

� IT resiliency (e.g., data governance, data and asset management, IT talent)

� ESG initial program assessment*

� Cloud services and storage (e.g., data security, business continuity)� Fraud

� Culture*

Operational model

� IA reporting content and delivery enhancements

� Blending methods for executing audits, including agile, D&A, etc.

� Operating with increased agility, especially during risk assessment and planning

� Staying close to the business in a virtual environment 

Digital acceleration

� Holistic strategy for refresh of technology stack to enable IA

� Data-driven enterprise risk assessment

� Focus on automation

� Continuous monitoring

� Stronger integration of second and third lines on common GRC technologies

� Process mining

Stakeholder engagement

� More subject matter expertise in IA, especially when working with first and second line

� Improve IA brand

� Changing demographic of AC

� Improving AC chair connectivity

� Resourcing needs across the organization 

Modern workforce

� Consideration of IA resources with ESG experience

� Hybrid service delivery models (in-house, external expertise, low-cost markets, centers of excellence

� Better integration of IA IT resources across the organization

� Need for more specialized or mature capabilities around data analytics and insights

� Upskilling IT and enterprise technology acumen

� Refreshing talent strategy to mitigate impacts of talent drain and resource needs

� Overall shift in skill sets needed given shifts in IA delivery model


Bold indicates new or continued signals for IA focus