AI is challenging the traditional hierarchies in technology, measurement, and talent. However, many uncertainties remain regarding the future of AI’s impact on business.
In 2026, Andy Sen, CTO of AppDirect, has told Digital Journal how the decentralization and democratisation of AI in business will progress. In particular, Sen envisages an explosion of AI tools and this will mark the end of the ERP era.
However, Sen also suspects that organisations will not be able to measure AI’s impact on the bottom line. Overall, Sen considers the future of AI innovation as talent-fluid – in other words, you no longer need to be an engineer to innovate.
The shift from ERPs to explosion of AI tools
In terms of enterprise resource planning, Sen sees a major contribution coming from AI: “We’re seeing the end of the big enterprise software suite era. While ERPs and similar systems won’t disappear, they’ll become less strategic. The focus is shifting to smaller, flexible AI-driven tools that evolve faster and can better match the pace of business.”
This will be in the form of new offerings. Here Sen foresees: “Expect an explosion of AI products next year – both consumer-facing and internal. Some of these solutions will inevitably overlap or even duplicate each other, but this is a good problem to have. In the early phases of AI development, this abundance of innovation will enable wide experimentation. Eventually, we will reach a point where consolidation makes sense. But for now the trend is clear: decentralized AI tools will outpace centralized systems.”
The ROI of AI in 2026
While firms will invest heavily into AI and expand the number of applications, there will not be any immediate ‘return on investment’. It’s a longer ball game, notes Sen: “In 2026, organizations still won’t be able to measure AI’s impact on the bottom line. Instead, we will see ROI measurement at the project level – how many transactions were AI-assisted, how many contracts were reviewed faster, how many deliveries were automated. With time, those incremental metrics will add up to something more transformative, but we can expect it to be a few more years before AI’s ROI shows up in traditional profit-and-loss terms.”
The future of AI innovation is talent-fluid
A key advantage of AI is with breaking down functional specialisms, observes Sen. As examples: “One of the biggest takeaways from this year is how fast AI is accelerating as its development becomes more decentralized. You no longer need to be an engineer to innovate. People across departments are creating tools that solve problems specific to their work, and that kind of innovation is something we’ve never seen before in enterprise tech.” In terms of how this innovation wave will manifest itself, Sen predicts: “This means the next wave of AI innovation won’t just come from the researchers building frontier models. Some of the biggest success stories will come from people who never saw themselves as ‘AI experts’ but had the outside perspective and imagination to apply it in powerful ways.”
