Intelligent Automation and Gen AI:  Time for Radical Transformation

Blog post

Intelligent Automation technologies, including GenAI, are driving a radical transformation of SG&A functions. The Hackett Group® predicts that GenAI could reduce SG&A costs by up to 40% over the next 5-7 years. This is tremendously exciting. However, it requires that decision makers understand  transformative Intelligent Automation technologies – their potential, where to apply, and how to manage risk.

Transformative Technologies: Be Smart About Intelligent Automation

Intelligent Automation is a category of advanced transformative technologies focused on optimizing structured, unstructured, and interactive work. Intelligent Automation technologies abound. Intelligent Automation is comprised of 6 types of automation: 

Automation Type Mimics Definition Degree of Adoption
Robotic Process Automation (RPA) Human actions Automates rules-based tasks on structured data 80%
Intelligent Data Capture Human interpretations Captures or extracts information from analog and digital inputs 49%
Conversational Assistants Human interactions Linguistic interactions and optimized conversations using Natural Language Processing, and Natural Language Generation 33%
Predictive AI Human intelligence Processes are structured, information is complex; provides insights, and predictions driven by algorithms 26%
Agile Orchestration Human work management Executes by established systems, and manual and digital labor (e.g.,  process mining, business process management, workflow) 30%
Generative AI Human thinking Provides context-based knowledge that can create content and enable autonomous operations 43%1
1:  41% in pilot programs and 2% deployed on a large scale

Success With AI Will Vary. Discipline Matters.

Organizations and decision makers need to find the right balance between speed and approach. Organizations that are adopting a more disciplined approach, while smaller in number, are expected to achieve a higher ROI while more effectively mitigating risks. 

Name Adoption Level Risk Benefit
Late Adopters – 30% of companies
– Waiting for technology to mature
Low Low
Experimenters – 60% of companies
– Entrepreneurial hot spots experiment throughout the organization
High Moderate
Disciplined Leaders – 10% of companies
– Disciplined approach with appointed leader that engages in disciplined AI processes
Low High

GenAI is Now Integral to The Finance Roadmap

Finance has a full agenda of priorities where Gen AI can begin to directly impact productivity. Examples of how finance teams are tactically utilizing Gen AI, at this stage in the cycle, include:

  • Internal audit, compliance review and reporting
  • Environmental, social and governance reporting
  • Creating alerts for new regulations with change summaries
  • Drafting responses to regulator queries
  • Drafting financial reports and summaries for internal and external reporting
  • Preparing earnings call scripts and earnings releases, and anticipating investor inquiries
  • Assisting in research for credit application reviewers
  • Preparing intelligent auto-responses
  • Performing tax calculations

Gen AI Use Case Benefits Will Accrue Over Time

AI has a broad range of applications in finance and accounting, helping professionals make more informed decisions, automate repetitive tasks, and improve overall efficiency. Examples include:

Intelligent Automation Use Cases Description Expected Benefits
Technical Accounting Research Scan accounting standards, regulations, and technical accounting guidance to generate position papers on the impact of new accounting standards on company financials under different scenarios – Faster turnaround time on technical accounting position papers
– Lower cost and effort associated with technical accounting research
– Shorter research cycle enables more proactive and informed response to new accounting regulations
– Stronger compliance with new accounting regulations
External Reporting Narrative and Disclosures Automate the creation of management discussion and analysis commentary and footnotes to explain financial results to investors in external report filings, earnings release communications and investor presentations – Shorter cycle time for narrative creation
– Lower external reporting costs
– Increased speed to release earnings and file external reports
– Narrative commentary can be leveraged for other purposes and audiences in multiple formats
Transaction Matching Analysis Analyze non-matching transactions, supporting documentation and historical data to detect patterns across divisions to create automated matching recommendations and better insights for decision making and process optimization – Faster reconciliation of intercompany accounts
– Lower cost and effort associated with intercompany accounting
– Greater automation in intercompany reconciliation
– Faster close cycle time
Journal Entry Creation Automatically create and post journal entries for common and high-volume transactions, generate and store supporting documentation – Higher automation of journal entries
– Lower cost and effort associated with general ledger accounting activities, including journal entry processing
– Faster close cycle time
Cost Allocation Scenario Modelling Analyze cost allocation history, consumption trends, transaction volumes and external market data to build cost allocation scenarios and recommended actions – Deeper insight into cost allocation and consumption trends
– Faster, more comprehensive analysis of cost consumption driving better, more informed decisions on allocation model
– Lower cost and effort associated with corporate allocations and cost modeling
– Ability to dynamically adjust allocation models as internal and external conditions change

Final Thoughts

When transforming a Finance process, assess the work by type and then eliminate, enable, and enhance: 

  • Structured work (organized in a set and repeatable pattern): eliminate through automation
  • Unstructured work (typically not organized in a set pattern): enable by adopting digital assistants
  • Interactive work (requires at least a two-way interaction between the user and system): enhance through personalization at scale

AI provides forward-thinking leaders and decision makers the opportunity to radically transform their finance and accounting service delivery model. GenAI will reduce FTEs in the transactional processes but bolster finance value-adding capabilities. It will require new specializations. Skill sets will be augmented. It will boost productivity. GenAI changes the conversations.

Written By: Bill Marchionni, Account-to-Report Advisory Global Program Leader, The Hackett Group

Read this Forbes article by Trintech CFO Omar Choucair, “Understanding How AI Fits Into Your Finance Function.”