Archive for category: News

As organizations race to adopt AI and cloud ERP, the real challenge isn’t the technology itself—it’s whether it actually helps people work better. In an article from Forbes, written by supply chain management expert Richard Howells, the focus shifts from digital transformation buzzwords to a more human definition of productivity. Howells argues that productivity has stalled because companies have spent decades designing systems around processes and metrics instead of people. Drawing on insights from Elisabetta Spontoni, Executive Vice President at Capgemini, Howells makes the case that cloud ERP and AI deliver value only when they align with how humans actually work.

Three practical principles stand out. First, AI solutions should be designed around real-world roles, not abstract capabilities. Embedding intelligence directly into daily workflows—such as surfacing supplier risk or sustainability impacts at the right moment—helps technology support better decisions without adding friction.

Second, simplification matters. Many ERP environments are weighed down by unused custom code that slows change and innovation. Moving to modular, cloud-based ERP makes it easier to evolve systems incrementally and adapt as business needs shift.

Third, data should empower employees, not overwhelm them. Clean, well-governed data builds trust, speeds decision-making, and helps people see the real impact of their work.

Ultimately, the article positions AI as a digital colleague—handling routine tasks, reducing noise, and freeing people to focus on what truly drives value. The future of productivity, it concludes, is more human, not more mechanical.

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AI (artificial intelligence) agents are set to become key members of the workforce by 2026, and ERP (enterprise resource planning) and HCM (human capital management) buyers need to prepare for this shift, according to Tarsilla Moura, Content Director at ERP Today. In a recent article Moura explains how enterprise software is moving from supporting just human workers to integrating AI agents that can independently handle tasks and processes. This change means businesses will need to update their tech stacks and rethink how they manage their workforce to stay competitive.

By 2026, the top HCM platforms are expected to add features that manage digital employees, or AI agents, who will take on complex tasks across multiple systems. These digital workers will become a core part of a hybrid human-AI workforce, improving everything from workforce planning to efficiency. Moura also predicts that many enterprise vendors will introduce Model Context Protocol (MCP) servers to allow AI agents to work across different platforms without being locked into one vendor. With rising AI regulations, ERP systems will also need to include features like explainable AI and real-time compliance monitoring to meet industry standards.

As AI-driven changes reshape the way we work, businesses will need to adapt their ERP systems to accommodate digital agents, ensuring their platforms can handle AI-powered workflows and governance. Those who move early will have a competitive edge, while lagging behind could risk falling short on compliance and efficiency.

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As the pace of business keeps accelerating, many CIOs are realizing that traditional ERP (enterprise resource planning) systems simply can’t keep up. In a recent article for CIO.com, enterprise technology leader Tirumala Rao Chimpiri makes the case that ERP needs to be reimagined—not as a rigid system of record, but as a flexible, composable backbone that supports constant change. For years, ERP has been the operational core of the enterprise. But monolithic architectures, heavy customization, and long upgrade cycles have turned many systems into bottlenecks rather than enablers. Chimpiri argues the problem isn’t ERP itself—it’s how organizations think about it. When ERP is treated as a one-time implementation instead of a living platform, agility suffers.

The alternative is composable ERP. Built on modular, cloud-native components and connected through APIs, this model lets organizations assemble capabilities as needed, integrate best-of-breed applications, and layer in AI for automation and insight. Instead of slowing the business down, ERP becomes something that evolves alongside it. A key shift is designing ERP around real people, not generic transactions. Persona-based experiences give leaders and teams the information they actually need—whether that’s real-time financial health, live supply chain signals, or operational performance—without forcing everyone into the same complex interface. Chimpiri is also clear that this transition takes more than new tools. Strong data governance, disciplined integration, security, and change management are essential. Above all, ERP modernization is a business transformation, not just an IT project.

Chimpiri ends with a simple thought: rethink ERP as a platform for innovation. Those who embrace composability will build resilience and agility into the enterprise. Those who don’t risk being held back by systems designed for a very different era.

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As artificial intelligence (AI) becomes more embedded in product development and operations, it’s reshaping not just factories, but the relationships between brands and the companies that build their products. In a recent Forbes article, senior contributor and CEO of AI-powered analysis platform Instrumental Anna-Katrina Shedletsky explores how data transparency is becoming a defining force in electronics manufacturing in the AI age. Historically, electronics manufacturing has operated on thin margins and “cost-plus” contracts, giving factories little incentive to share detailed production data. Full transparency can expose efficiencies or issues that brands might use to renegotiate pricing, making manufacturers understandably cautious. As Arch Systems CEO Andrew Scheuermann points out, when margins can be as low as two percent, unrestricted data sharing can feel existential. AI is beginning to shift that dynamic. Brands are investing in large data sets that combine design, manufacturing, and returns information to improve product quality and customer experience. To unlock that value, manufacturers must move beyond one-off reports toward more open, continuous data sharing—forcing both sides to rethink trust, accountability, and partnership models.

The article highlights Logitech as an example of this evolution. Led by global quality and manufacturing head Martin Hess Pedersen, Logitech treats manufacturers as partners rather than suppliers. Contracts share risk, while transparency flows both ways: factories gain insight into consumer sentiment, return rates, and product performance, creating a powerful feedback loop between the factory floor and the customer. AI accelerates this shift by enabling collaborative problem-solving, from temporary, task-specific data use to “closed-loop quality” systems that connect factory data with real-world usage. The payoff is faster innovation, higher quality, and stronger partnerships—driven as much by trust as by technology.

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