After testing AI tools for a few years, enterprises are ready to focus on the ones that have delivered results, TechCrunch reported Tuesday (Dec. 30), citing its survey of 24 VCs.
The areas in which some of the VCs said they expect enterprises to concentrate their budgets include AI safeguards and oversight, data foundations, model post-training optimization, consolidation of tools, vertical solutions and products built on proprietary data, according to the report.
PYMNTS reported Dec. 9 that a report from OpenAI showed that the era of AI experimentation in business is over and that generative AI is becoming embedded, mission-critical infrastructure within the global financial and digital economy.
Organizations are moving beyond pilot programs to scaled, operational deployment, as evidenced by OpenAI’s findings that compared to a year ago, the average enterprise worker now sends 30% more ChatGPT messages weekly, the average API reasoning token consumption is 320 times higher, and the number of workplace seats now using ChatGPT Enterprise is nine times higher.
PYMNTS reported in April that the most effective enterprise AI implementations typically address specific business problems rather than pursuing technology for its own sake and that the implementation of enterprise AI is typically done in stages, starting with identifying use cases with the highest impact, building proofs of concept and deploying it at scale.
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The PYMNTS Intelligence report “Smart Spending: How AI is Transforming Financial Decision Making” found that 82% of chief financial officers at U.S. firms with over $1 billion in annual revenues are either already using or actively considering adopting AI for accounts payable functions.
These CFOs reported that the tangible benefits of the technology include reducing costs, preventing payment errors and optimizing working capital. They also said AI supports functions including payment scheduling, predictive cash flow analytics, procurement cost control and risk management.
The report found that the collective demand from CFOs for the technology signals a shift toward AI-driven financial management.
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