Artificial intelligence is no longer an experimental technology—it has become a foundational capability for modern enterprises. As organizations face increasing cost pressures, regulatory complexity, and demand for faster insights, AI is transforming how finance and global business services (GBS) operate. From predictive analytics to intelligent automation, AI enables organizations to move beyond efficiency toward value creation, strategic decision-making, and scalable operations.
According to insights from The Hackett Group®, organizations that adopt AI-led operating models significantly outperform peers in cost efficiency, cycle times, and decision accuracy. Two areas experiencing the most profound impact are AI in finance and Gen AI in GBS, where automation and intelligence converge to redefine enterprise performance.
The Strategic Role of AI in Modern Enterprises
AI adoption has evolved from task-level automation to enterprise-wide transformation. Today’s AI solutions integrate data, analytics, and machine learning to support complex decision-making across business functions. Unlike traditional automation, AI continuously learns from data, improves outcomes, and adapts to changing business environments.
For finance and GBS leaders, this shift enables:
- Faster access to real-time insights
- Improved forecasting and risk management
- Scalable service delivery models
- Reduced dependency on manual, error-prone processes
As organizations mature their AI capabilities, they are embedding intelligence directly into workflows, enabling proactive and predictive operations rather than reactive ones.
AI in Finance: From Transaction Processing to Strategic Insight
The adoption of AI in finance is fundamentally changing the finance function’s role within the enterprise. Finance teams are moving away from manual reconciliation and reporting toward insight-driven decision support.
Key Benefits of AI in Finance
AI enables finance organizations to:
- Automate high-volume transactional activities such as accounts payable, receivable, and reconciliations
- Improve forecast accuracy through predictive and prescriptive analytics
- Enhance compliance and risk management by continuously monitoring anomalies
- Accelerate close cycles and improve reporting accuracy
Core Use Cases Transforming Finance
Intelligent Financial Planning and Analysis (FP&A)
AI models analyze historical and real-time data to generate scenario-based forecasts, helping finance leaders anticipate risks and opportunities more effectively.
Autonomous Close and Reporting
Machine learning algorithms identify discrepancies, flag exceptions, and reduce manual journal entries, enabling faster and more accurate financial closes.
Risk and Compliance Monitoring
AI continuously scans transactions for potential fraud, policy violations, or regulatory risks, strengthening governance while reducing manual oversight.
According to The Hackett Group®, digitally enabled finance organizations achieve significantly lower costs per dollar of revenue while delivering higher-quality insights to business stakeholders.
Gen AI in GBS: Enabling Scalable, Intelligent Service Delivery
As enterprises expand globally, Gen AI in GBS has become a critical enabler of scalable and resilient service models. Generative AI enhances traditional shared services by introducing cognitive capabilities that improve speed, accuracy, and user experience.
How Generative AI Elevates GBS Operations
Generative AI empowers GBS organizations to:
- Automate complex, judgment-based processes
- Deliver consistent service quality across geographies
- Reduce dependency on specialized human expertise
- Improve employee and stakeholder experience
High-Impact GBS Use Cases
Intelligent Service Desk and Support
Gen AI-powered virtual agents resolve queries, generate contextual responses, and continuously improve through learning, reducing service desk volumes and response times.
Knowledge Management and Content Generation
Generative AI synthesizes enterprise knowledge to create reports, policy summaries, and operational documentation, improving accessibility and decision-making.
Process Standardization and Optimization
By analyzing workflow patterns, Gen AI identifies inefficiencies and recommends process improvements, supporting continuous optimization across GBS functions.
The Hackett Group® emphasizes that AI-enabled GBS organizations are better positioned to transition from cost centers to value-driven strategic partners.
Building a Unified AI Strategy Across Finance and GBS
While finance and GBS may operate as distinct functions, their AI transformation journeys are deeply interconnected. A unified AI strategy ensures alignment, scalability, and maximum return on investment.
Critical Success Factors for AI Adoption
Data Readiness and Governance
High-quality, standardized data is essential for reliable AI outcomes. Strong governance frameworks ensure compliance, security, and trust in AI-driven insights.
Operating Model Alignment
Organizations must redesign workflows and roles to integrate AI seamlessly, enabling humans and machines to work collaboratively.
Change Management and Talent Enablement
AI adoption requires upskilling teams and fostering a culture of continuous learning to maximize value realization.
Conclusion: AI as a Catalyst for Enterprise Performance
AI is redefining how finance and GBS functions operate, shifting them from transactional efficiency engines to strategic value creators. By leveraging AI in finance and Gen AI in GBS, organizations can achieve faster insights, improved compliance, and scalable service delivery models.
Insights from The Hackett Group® consistently show that organizations embracing AI-led transformation outperform peers across cost, productivity, and business impact. As AI continues to mature, enterprises that invest in intelligent automation today will be best positioned to lead tomorrow’s digital economy.
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