Can finance leaders turn confidence into growth?
Chapter 2Finance leaders want to focus on strategy, but day-to-day demands still take up much of their time.
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Chapter 3
More than half of finance leaders report measurable benefits from AI investments, although only 8% have achieved significant value. As adoption matures, the priority is shifting from individual use cases to integrated, enterprise-scale transformation.
Finance leaders are increasing their commitment to AI, automation and broader finance transformation. Over the next year, 75% of respondents plan to devote more time and resources to adopting AI and automation.
Early investments are beginning to produce results. More than half of respondents report measurable benefits from AI over the past 12 to 24 months, although only 8% describe the impact as significant. For most organisations, the gains remain moderate or limited, suggesting that AI is creating value but has not yet transformed financial performance at scale.
Many organisations are applying AI to selected activities such as transaction matching, forecasting, reporting and controls. These use cases can improve productivity and decision-making, but their impact remains concentrated within individual tasks or processes.
The next stage will require finance functions to move beyond isolated applications and integrate AI across end-to-end workflows. This means combining AI adoption with process redesign, stronger data foundations, clear ownership and appropriate governance.
Select data set:
More than half of finance leaders (54%) report a measurable impact from AI investments over the past 12-24 months, with 23% reporting moderate improvements, 23% reporting limited improvements, and 8% reporting significant benefits.
At the same time, relatively few organisations (9%) report no measurable impact. However, the findings also suggest that AI adoption remains in its early stages across many finance functions. Nearly one in five respondents (18%) say it is too early to assess results, while a further 17% report that they have not yet made meaningful AI investments.
The results indicate that AI is already creating value across finance organisations, but that the majority of benefits achieved so far are incremental rather than transformational. This is consistent with many organisations focusing initial AI deployments on specific use cases such as forecasting, reporting, controls and operational efficiency, rather than reimagining end-to-end finance processes.
As finance functions mature their AI capabilities, the opportunity will shift from isolated productivity gains to broader process redesign, improved decision support and more scalable operating models. Organisations that combine AI with strong data foundations, process standardisation, and clear business ownership are likely to realise greater, more sustainable value.
AI may improve activities such as matching, forecasting or reporting. However, without redesigning the wider process, these gains may not translate into a significant improvement in overall financial performance.
Without clear baselines, defined targets and mechanisms to track outcomes, organisations may find it difficult to demonstrate the full value generated by successful AI deployments.
Nearly 18% of respondents say it is too early to assess the impact of AI, while 17% report that they have not yet made meaningful investments.
Many finance functions are still building the data, systems and process foundations needed to scale AI beyond individual use cases. Until AI is integrated across end-to-end workflows, its value is more likely to manifest as targeted gains in productivity and efficiency than as broader transformation.
Most finance functions have moved well beyond basic digitisation. 68% are planning or considering a transformation. Meanwhile, 14% are operating fully integrated environments where transformation is already underway.
Modernisation, however, remains incomplete. Integrating systems, standardising data and simplifying underlying processes will be the key to supporting broader, more measurable AI deployment.
Early in the journey or with no clear transformation plans
Planning and considering transformation
Actively executing in an integrated environment
The next phase of AI leadership will be less about the number of tools an organisation adopts and more about its ability to turn selected use cases into a finance operating model that works at scale.
Start with high-friction, high-value use cases where the benefit can be measured clearly
Establish a baseline and define the outcome before implementation
Standardise underlying data and processes before scaling
Build governance, controls, and accountability into the workflow
Expand only after adoption and benefits are proven
The priority for CFOs is to move beyond isolated experiments and integrate AI in core finance processes and decision-making, with a clear focus on measurable value creation.
Every organisation’s journey is different. Our experts work with finance leaders to navigate evolving priorities, from technology enablement and process transformation to strengthening strategic decision-making.
Let’s discuss what the next chapter of your finance function could look like.
The India Finance Leaders Barometer 2026 by Grant Thornton Bharat captures the perspectives of CFOs and senior finance leaders on the priorities, challenges and opportunities shaping the finance function.
Drawing on insights from across industries, the survey explores how finance leaders are responding to an increasingly dynamic business environment and where they expect the function to evolve over the coming years.

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Finance leaders want to focus on strategy, but day-to-day demands still take up much of their time.
Finance leaders want to focus on strategy, but day-to-day demands still take up much of their time.