Artificial intelligence in finance: from performance-oriented execution to lean, strategic CFO leadership
Learn how CFOs can supercharge finance functions in this brochure that shares the potential and challenges of capitalizing on AI. Download the DocumentArtificial intelligence in finance
From performance-oriented execution to
lean, strategic CFO leadership
Finance | SAP Business AI
From performance-oriented execution to
lean, strategic CFO leadership
Finance | SAP Business AI
3 | 16Artificial intelligence in finance
Dear readers,
Across all industries, CFOs are facing an unprecedented rate of change. Regulatory requirements
are becoming ever more excruciating, digital transformation is accelerating, and customers are
more demanding than ever. Add to this list the realities of growing geopolitical tensions, shifting
socio-economic landscapes, and increased market volatility.
Yet, rather than just challenges, we see opportunities, too—particularly in the area of AI. Today, we
find ourselves in the middle of an intelligence revolution that is transforming businesses and
economies, not unlike the Industrial Revolution of the 18th and 19th centuries. I’m excited about
what AI can do for us, our finance functions, our businesses, and our societies.
As CFO at SAP, I have had the privilege of leading SAP through record-breaking growth—growth
that is both accompanied and enabled by SAP Business AI innovations in our portfolio. My teams
are among the first to have witnessed, used, and benefited from AI built specifically for finance.
Based on this experience, I envision CFOs everywhere transforming from the performance-focused
orientation we’ve maintained for years to new roles, functions, and capacities based on lean,
strategic finance operations. This will be a multi-year journey, but we are already beginning to see
the fruits of our efforts.
This document shares these AI innovations with you. Each, in their own way, has the potential to
bring out the best for your finance team. I hope your organization is inspired by SAP’s vision of AI
helping power the future of finance, and we look forward to discussing this vision in greater depth
with you. Thank you for your trust and partnership.
Dominik Asam
CFO and member of the Executive Board, SAP SE
A foreword by the SAP CFO
Dear readers,
Across all industries, CFOs are facing an unprecedented rate of change. Regulatory requirements
are becoming ever more excruciating, digital transformation is accelerating, and customers are
more demanding than ever. Add to this list the realities of growing geopolitical tensions, shifting
socio-economic landscapes, and increased market volatility.
Yet, rather than just challenges, we see opportunities, too—particularly in the area of AI. Today, we
find ourselves in the middle of an intelligence revolution that is transforming businesses and
economies, not unlike the Industrial Revolution of the 18th and 19th centuries. I’m excited about
what AI can do for us, our finance functions, our businesses, and our societies.
As CFO at SAP, I have had the privilege of leading SAP through record-breaking growth—growth
that is both accompanied and enabled by SAP Business AI innovations in our portfolio. My teams
are among the first to have witnessed, used, and benefited from AI built specifically for finance.
Based on this experience, I envision CFOs everywhere transforming from the performance-focused
orientation we’ve maintained for years to new roles, functions, and capacities based on lean,
strategic finance operations. This will be a multi-year journey, but we are already beginning to see
the fruits of our efforts.
This document shares these AI innovations with you. Each, in their own way, has the potential to
bring out the best for your finance team. I hope your organization is inspired by SAP’s vision of AI
helping power the future of finance, and we look forward to discussing this vision in greater depth
with you. Thank you for your trust and partnership.
Dominik Asam
CFO and member of the Executive Board, SAP SE
A foreword by the SAP CFO
4 | 16Artificial intelligence in finance
How CFOs can capitalize on AI
Supercharge your finance functions with embedded AI
At SAP, we believe it can—if properly
deployed.
A 2025 survey by Boston Consulting Group’s (BCG)
Center for CFO Excellence, “How to Get ROI from AI in
the Finance Function,” shows that AI adoption in finance
is rising. Enthusiasm for the technology is high, with
about half of finance leaders expecting breakthrough
results over the next three years. Yet for now many
organizations are falling short of the meaningful returns
they expected—achieving around 10% ROI compared
to the 20% they’re targeting. The issue isn’t lack of
interest or effort, but rather how organizations realize
value. Those that prioritize value from the outset and
focus on practical outcomes are more likely to reap
strong ROI.1
For AI to be effective in finance, it must be integrated into
the right business applications and processes and
trained on trusted, relevant data. This is a pre-requisite
to making AI an always-on, always-available domain
resource for everyone on the CFO team.
This is why at SAP we’re embedding advanced AI
capabilities into our Cloud ERP solutions. Our aim is to
empower finance professionals with powerful, context-
aware decision-making capabilities—and our vision is
finance transformation with help from AI. With SAP
solutions and embedded AI, your CFO team can not only
streamline finance operations, but also transition from
the role of an internal service provider to that of a
strategic partner helping drive business success.
CFOs face immense pressure to streamline operations and deliver strategic value.
In April 2025, the IMF’s 2025 World Economic Outlook revised its January
prediction of 3.3% growth downward to 2.8%—a 15% decrease. While 2026
growth expectations are more hopeful at 3%, this recovery erases only half of the
2025 drop. From navigating volatile markets to heading off supply chain
disruptions and managing sustainability, CFOs need new tools. Can AI help?
How CFOs can capitalize on AI
Supercharge your finance functions with embedded AI
At SAP, we believe it can—if properly
deployed.
A 2025 survey by Boston Consulting Group’s (BCG)
Center for CFO Excellence, “How to Get ROI from AI in
the Finance Function,” shows that AI adoption in finance
is rising. Enthusiasm for the technology is high, with
about half of finance leaders expecting breakthrough
results over the next three years. Yet for now many
organizations are falling short of the meaningful returns
they expected—achieving around 10% ROI compared
to the 20% they’re targeting. The issue isn’t lack of
interest or effort, but rather how organizations realize
value. Those that prioritize value from the outset and
focus on practical outcomes are more likely to reap
strong ROI.1
For AI to be effective in finance, it must be integrated into
the right business applications and processes and
trained on trusted, relevant data. This is a pre-requisite
to making AI an always-on, always-available domain
resource for everyone on the CFO team.
This is why at SAP we’re embedding advanced AI
capabilities into our Cloud ERP solutions. Our aim is to
empower finance professionals with powerful, context-
aware decision-making capabilities—and our vision is
finance transformation with help from AI. With SAP
solutions and embedded AI, your CFO team can not only
streamline finance operations, but also transition from
the role of an internal service provider to that of a
strategic partner helping drive business success.
CFOs face immense pressure to streamline operations and deliver strategic value.
In April 2025, the IMF’s 2025 World Economic Outlook revised its January
prediction of 3.3% growth downward to 2.8%—a 15% decrease. While 2026
growth expectations are more hopeful at 3%, this recovery erases only half of the
2025 drop. From navigating volatile markets to heading off supply chain
disruptions and managing sustainability, CFOs need new tools. Can AI help?
5 | 16Artificial intelligence in finance
The challenge:
AI integration
Realizing the promise of AI for finance
teams isn’t as simple as flipping a switch.
Finance leaders looking to get the most out of AI face
several significant hurdles that must be carefully
navigated.
Data quality
AI systems are only as good as the data they’re trained
on, and many organizations struggle with inconsistent,
unreliable, or outdated financial information spread
across multiple systems. Without a solid foundation of
clean, standardized data, AI implementations risk
becoming expensive experiments that deliver limited
value.
Organizational readiness
Many finance departments still use on-premises systems
that they’ve customized over the years to meet their
specific business needs. These legacy environments can
make it difficult to integrate new AI capabilities
effectively. Moreover, scaling AI solutions across
different regions, business units, and processes requires
careful orchestration of technology infrastructure and
organizational change.
Regulatory volatility
Global AI regulations are evolving rapidly, with different
regions adopting varying approaches to AI governance.
Finance leaders must ensure their AI not only delivers
business value, but also maintains compliance with
these emerging requirements. The swift advancement of
technologies like large language models (LLMs) further
complicates this picture, as regulations struggle to keep
pace with innovation.
Yet these challenges are not impossible to overcome.
They simply underscore the importance of choosing the
right partner and approach to AI adoption—one that
combines robust technology infrastructure with deep
domain expertise and a clear understanding of
regulatory requirements. Only by addressing these
challenges can your finance organization expect to reap
the benefits of AI for finance.
5 | 16
The challenge:
AI integration
Realizing the promise of AI for finance
teams isn’t as simple as flipping a switch.
Finance leaders looking to get the most out of AI face
several significant hurdles that must be carefully
navigated.
Data quality
AI systems are only as good as the data they’re trained
on, and many organizations struggle with inconsistent,
unreliable, or outdated financial information spread
across multiple systems. Without a solid foundation of
clean, standardized data, AI implementations risk
becoming expensive experiments that deliver limited
value.
Organizational readiness
Many finance departments still use on-premises systems
that they’ve customized over the years to meet their
specific business needs. These legacy environments can
make it difficult to integrate new AI capabilities
effectively. Moreover, scaling AI solutions across
different regions, business units, and processes requires
careful orchestration of technology infrastructure and
organizational change.
Regulatory volatility
Global AI regulations are evolving rapidly, with different
regions adopting varying approaches to AI governance.
Finance leaders must ensure their AI not only delivers
business value, but also maintains compliance with
these emerging requirements. The swift advancement of
technologies like large language models (LLMs) further
complicates this picture, as regulations struggle to keep
pace with innovation.
Yet these challenges are not impossible to overcome.
They simply underscore the importance of choosing the
right partner and approach to AI adoption—one that
combines robust technology infrastructure with deep
domain expertise and a clear understanding of
regulatory requirements. Only by addressing these
challenges can your finance organization expect to reap
the benefits of AI for finance.
5 | 16