to Finance headsthe technology The challenge is no longer a lack of options. It is surplus to them.
An expanded list of chief financial officers is presented artificial intelligence Tools, real-time payment capabilities, forecasting platforms, treasury systems, and automation products, each promising faster decision-making, greater efficiency or more control. Pressure to act is mounting as competitors announce pilots and boards of directors question how the company will use artificial intelligence. But the greatest risk facing financial leaders is that they will invest in technology without first defining what that investment is supposed to achieve.
“If you start by defining the outcomes you want to achieve, whether that’s better liquidity visibility, stronger controls, greater efficiency, or faster decision-making, and then evaluate the technology against those goals, that will really help move you in the right direction.” Matthew DaviesHead of Global Payments Solutions EMEA, and Global Co-Head of Enterprise Sales at GTS Bank of Americahe told PYMNTS for the 2026 PYMNTS Original Series “Summer School.”
“The biggest risk and challenge is misinvestment, not lack of investment,” Davis said. “You need to get rid of them and focus on solving specific business challenges, not just delivering the latest shiny technology.”
This distinction is particularly important as payments, Data AI is becoming more interconnected. Modern payment infrastructure produces the real-time information that AI systems need. Better data improves forecasting and controls. Automation creates the capacity for higher value work. But none of these benefits can be achieved without integration, governance and adoption.
Discipline seems clear. In practice, it is often lost.
The 2026 CFO Tech Test focuses on value, not hype
While CFOs have broader responsibility for liquidity, operational agility, data management and technology returns, the fintech rules of the game are less about keeping up with every new capability and more about creating the conditions under which innovation can produce measurable value.
“You want to prioritize those solutions that have proven real-world use cases and measurable business impact,” Davis said. “If you don’t take the right measures in advance, how can you judge the results of your decisions?”
Successful modernization requires collaboration between the treasury, finance, technology, cybersecurity, data and risk sectors. It also requires change management, implementation support, and an incremental approach that expands capabilities only when value is proven.
“The real test for CFOs in 2026 is not keeping up with innovation,” Davis said. “It’s about identifying investments that enhance visibility, liquidity and decision-making while delivering measurable business value.”
This shift reflects a more volatile macro environment. Companies manage liquidity across multiple markets, currencies, banks and legal entities while responding to geopolitical disruptions, changing interest rates and complex fraud threats.
“Payments are increasingly viewed as a strategic enabler of liquidity management, risk control and, frankly, enterprise-wide efficiency rather than just a historically office-based facility-type process,” Davies said.
Near-real-time visibility into cash positions allows treasury teams to make financing and investment decisions faster. It can also help companies move liquidity where it is needed without waiting for piecemeal reports or reconciliation at the end of the day. But the biggest opportunity lies in the data surrounding payment.
“Treasury teams increasingly rely on payments and data about payments to help them get their work done cash flow “Forecasting, capital allocation and strategic planning decisions,” Davis said.
Automate what is repetitive, not what is strategic
As financial data feeds enterprise AI systems, payment infrastructure becomes part of an enterprise’s financial intelligence system. But fragmented data across ERP systems, treasury platforms, bank portals, and acquired companies limits the effectiveness of any advanced technology sitting on top.
“If you don’t have high-quality, unified data, you don’t have the foundation you need for effective automation, forecasting, financial decision-making, and ultimately, any AI solution you want to put on top of it,” Davis said.
“Many organizations are discovering that improving data quality creates value in itself, even before they start planning the technology infrastructure they will put on top of it,” he added.
A financial leader cannot make a high-risk liquidity or capital allocation decision with conviction if cash positions are incomplete, definitions vary across systems or information must be manually reconciled before it can be trusted. For CFOs, this changes the update sequence. A higher-return AI initiative might start with data consolidation, systems integration, and control design rather than a high-level pilot experiment.
“The most immediate opportunity is to automate those repetitive manual tasks (and) improve operational efficiency across financial operations,” Davis said.
When finance teams spend less time compiling reports, reconciling transactions, and resolving routine exceptions, they can devote more attention to cash forecasting, scenario planning, risk assessment, and supporting strategic decisions.
“The goal is not AI for the sake of AI,” Davis said. “It’s really looking at AI and applying it where it solves real business challenges and delivers measurable value.”
a witness FULL INTERVIEW WITH PYMNTS TV’SUMMER SCHOOL. With Matthew Davies to hear more about:
- Why is the biggest technology risk for CFOs poor investment, not underinvestment? Davies explained why financial sector leaders should start with clearly defined business outcomes, such as stronger liquidity visibility, better controls and faster decisions, rather than chasing the latest technology.
- How modern payments and better data are becoming strategic finance infrastructure. The discussion explored how real-time visibility into payments can improve cash forecasting, capital allocation and risk management, while consolidated data creates the foundation for automation, artificial intelligence and more confident decision-making.
- Where there is potential. Davies said the clearest near-term opportunity lies in the automation of repetitive financial processes, but warns that disconnected pilots, weak governance and underutilized tools can leave companies with more complexity than generating measurable returns.
