In an era where speed, accuracy, and insight are the currencies of competitive advantage, generative artificial intelligence (Gen AI) is rapidly transforming finance operations. The Hackett Group is at the forefront of enabling this shift, offering end-to-end Gen AI services tailored for finance—from strategic consulting to development, deployment, and beyond. With proven tools, rigorous assessments, and a track record of measurable results, organizations can now unlock value across planning, reporting, compliance, auditing, cash flow, and more.
In this blog, we dive into how Gen AI is reshaping finance, the services and solutions available, and what it takes to adopt these technologies responsibly and successfully.
Why Generative AI Matters in Finance
According to The Hackett Group’s recent findings from their Key Issues Study (2025), many finance teams are already piloting Gen AI in core areas:
- 52% are using it for annual planning and forecasting
- 48% for business performance reporting and analysis
- 35% for strategic business planning
- 26% for general accounting and financial close
These adoption numbers reflect a strong trend: Gen AI is no longer just hype. Organizations see tangible benefits in automating repetitive tasks, improving decision-making with better data analysis, accelerating business cycles, and reducing manual errors.
Key Services for Finance Transformation with Gen AI
The Hackett Group offers several core services to help finance functions harness Gen AI in a structured, scalable, and responsible way:
1. Strategy Development
Working closely with finance leadership, this involves defining a Gen AI strategy that aligns with business goals. It includes evaluating existing capabilities, identifying high-impact use cases, and charting a scalable roadmap. Responsible AI practices and governance are central from the start.
2. Readiness & Gap Assessment
Before diving in, an organization’s readiness must be understood—technologically, organizationally, data-wise, skill-wise, and governance-wise. This assessment exposes gaps and frames the path forward so solutions can be implemented securely, compliantly, and effectively.
3. Use Case Identification & Prioritization
Not every finance process is equally suitable for Gen AI. Using platforms like AI XPLR™, The Hackett Group evaluates workflows, data quality, AI readiness, and business value to pick and rank use cases that will deliver maximum impact. This helps avoid low ROI experiments and focuses on what matters most.
4. Data Engineering
Enabling AI depends heavily on good data. The Hackett Group helps build scalable, enterprise-grade data pipelines (for example, using platforms like Snowflake or Databricks), transforms raw data (financial transactions, operational metrics, journal entries) into AI-ready forms, and establishes governance frameworks that support analytics, automation, and decision intelligence.
5. Custom Solution & AI Agent Development
Here’s where the rubber meets the road. The Hackett Group develops proofs of concept (PoCs), minimum viable products (MVPs), and ultimately full-scale solutions—such as automations for variance analysis, forecast narrative generation, auditing documentation, reconciliation, etc. AI agents are built to plug into functions like treasury, payables/receivables, expense management, general accounting, etc.
6. Monitoring, Optimization & Scaling
Deploying a Gen AI solution isn’t the end—it’s just the beginning. Continuous monitoring, performance tracking, feedback loops, upgrades, and optimizations ensure that solutions evolve as business needs, data, and technologies change.
Critical Enablers for Successful Gen AI Adoption
Deploying Gen AI in finance is not without its challenges. To get it right, organizations need to focus on several enablers:
- Ethics, Governance & Responsible AI
Gen AI introduces risks—bias, data leakage, compliance issues. From the start, there must be policies, oversight, and responsible-AI practices in place. The Hackett Group emphasizes embedding these into strategy and solution design. - Data Quality & Infrastructure
Garbage in, garbage out. Reliable data sources, clean data, strong pipelines, secure storage, proper architecture—all are non-negotiable. Platforms like Snowflake, Databricks are used to scale and standardize data engineering. - Talent & Change Management
Technology alone won’t transform finance. Teams need training, new ways of working, clarity on roles. Change must be managed across people, process, and culture. Hackett supports workforce readiness as part of the journey. - Scalable & Integrated Solutions
Solutions should be built for enterprise scale and integrate smoothly with existing systems (ERP, EPM, accounting systems etc.), workflows, and data environments. AI agents shouldn’t become silos. - Continuous Improvement and Monitoring
As business needs shift, regulations evolve, and models drift, monitoring and adaptability are key. Ongoing performance tracking, feedback loops, updates to models and workflows.
The Hackett Group’s Differentiators & Tools
What sets The Hackett Group apart in this space? Here are some of its distinguishing strengths and tools:
- AI XPLR™ – An analytics and benchmarking platform that integrates performance data (Digital World Class®) to quantify Gen AI opportunity and produce readiness assessments plus implementation roadmaps.
- ZBrain™ – A flexible orchestration platform allowing the deployment of custom AI agents and solutions; supports connecting LLMs with structured and unstructured data, building agents for finance workflows.
- Proprietary Benchmarking and Research – Based on Digital World Class® research and thousands of studies, giving evidence-based guidance and data to support prioritization and investment decisions.
- Responsible AI Focus – From security, compliance, data governance, to ethical considerations, their services embed responsibility throughout the AI lifecycle.
Measuring the Value: What Outcomes to Expect
Finance leaders implementing Gen AI can look forward to tangible business outcomes:
- Higher staff productivity and reduced manual workload
- Faster close cycles, more accurate reporting
- Improved forecasting and scenario planning
- Reduced error rates, better compliance, reduced risk
- Enhanced transparency, decision intelligence, and responsiveness
- Lower operational costs through automation of routine tasks
According to research cited by The Hackett Group, Gen AI has the potential to increase staff productivity by 44% in finance operations.
Getting Started: A Roadmap for Finance Leaders
If you’re considering Gen AI for your finance function, here’s a simplified roadmap:
- Assess your starting point – Evaluate data maturity, team skills, systems, governance.
- Define goals & use cases – What are your biggest pain points? Which processes offer the most leverage?
- Build the strategy & roadmap – Using tools & benchmarks, estimate impact, prioritize, plan phases.
- Pilot small but meaningful projects – Use PoCs or MVPs to test feasibility, measure gains.
- Deploy & scale – Integrate with systems, scale successful pilots, ensure infrastructure supports growth.
- Monitor & iterate – Use performance metrics, feedback loops, improve models; stay compliant and secure.
Conclusion
Generative AI is reshaping finance, moving beyond hype toward real transformation. With the right strategy, data foundation, governance, talent, and tools, finance organizations can unlock powerful gains: faster processes, deeper insights, reduced costs, and stronger compliance.
The Hackett Group offers a complete suite of services—from strategy and readiness assessment to custom AI agent development and scaling—with proprietary tools like AI XPLR™ and ZBrain™ to guide you. If you’re ready to accelerate your finance operations with Gen AI, the time is now.
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