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Generative AI For Finance: Lead adoption for powerful outcomes

CFOs and finance leaders are best positioned to lead GenAI integration across the enterprise, championing  projects that create the most profitable growth​

AI for finance guides the path forward while weighing urgency and risk awareness

AI in corporate finance makes business sense. The finance function is a good starting point for implementing generative AI. The pioneering approach optimizes intricate financial strategies and decision-making processes, enhancing efficiency, accuracy, and adaptability in the dynamic world of finance. As the “tip of the spear” in generative AI, finance can build the strategy that fully considers all the opportunities, risks, and tradeoffs from adopting generative AI for finance.   

However, it's crucial to acknowledge hurdles such as security, reliability, safeguarding intellectual property, and understanding outcomes. Armed with appropriate strategies, generative AI can elevate your institution’s reputation for finance and AI. Successfully adopting generative AI requires a balanced approach that combines urgency and risk awareness. The finance domain can pave the way by establishing an organizational framework that is aligned with your company's risk tolerance, cultural intricacies, and appetite for technology-driven change.

Generative AI for finance helps organizations accelerate their path to greater efficiency, accuracy, and adoptability. Similar to how we’ve shared AI Finance use cases, some possible use cases for Generative AI in Finance include:

  1. Developing forecasts and budgets with generative AI
    Per a survey conducted by KPMG, 83% of respondents use AI for financial planning, including predictive models, scenario creation, and budget insights.
  2. Generating AI-produced financial commentary and presentations
    The tech can cut time and effort for generating recurring financial reports, automatically importing data into templates, and automatically generating insights from data for finance and business.
  3. Gathering market intelligence using a large language model
    Generative AI’s large language model can leverage public data to create market insights, generate competitive intelligence, and develop customer insights using customizable analyses for regions or analyzed by personas.
  4. Producing strategic insights from data
    Analyze data for customer relationship management (CRM) or enterprise resource planning (ERP) insights. Then leverage for strategic decisions about finance, solve pricing/performance issues, or apply to another business task.
  5. Managing contracts with help from an AI tool
    Use generative AI to generate contracts, focusing on non-standard terms, identifying revenue-related clauses, and documenting accounting treatment.
  6. Detecting anomalies/fraud protection with generative AI
    Generative AI detects errors, spots fraud by analyzing data anomalies, and improves financials through ongoing transaction monitoring.

Generative Al's large language models applied to the financial realm marks a significant leap forward. With generative AI for finance at the forefront, this new AI technology guides the path towards strategic integration while addressing the accompanying challenges, ultimately driving transformative growth.

Dive into our thinking:

Generative AI guidance for CFOs

Learn how CFOs are fast-tracking the future of finance.

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