“It’s clearly dawned on OpenText that Vertica was probably the jewel in the Micro Focus crown,” Pelz-Sharpe said. “They’ve got a much more cohesive story on unstructured and structured data in the world of AI, and that there are real integrations with Vertica, into Aviators [and other services]. They’ve done a lot in a year.”
Agentforce isn’t the “big-bang” innovation that Salesforce CEO Marc Benioff characterized it as, according to both Opus Research founder Dan Miller and Deep Analysis founder Alan Pelz-Sharpe. “If you’re looking for the ability to route questions quickly via a decision tree to existing automation at scale — and you can find value in that — then sure, it’s useful,” Pelz-Sharpe said. “It takes [Einstein] Copilot from assistant duties toward an easier-to-measure and therefore easier-to-calculate, value role that connects customers with automation. That will help move projects from the whiteboard to checkbook for Salesforce and their partners,” he said.
\In the ever-evolving landscape of technology, one thing remains constant: hype. If you’re still catching your breath from the excitement surrounding generative AI (GenAI), brace yourself, because the future waits for no one. While GenAI continues to make waves, a new contender is quietly stepping onto the stage—Agentic AI—or, as many prefer, agent-based AI (because “agentic” sounds a bit peculiar, doesn’t it?). Regardless of the name, this next phase in AI promises to bring both hope and a host of challenging questions. The biggest one? Should you care about Agentic AI?
Alan Pelz-Sharpe, founder of market research firm Deep Analysis, also said he believes Microsoft and Google’s spat likely won’t affect buyer’s views of the two cloud providers, even though Microsoft’s claims about Google’s astroturf lobbying practices to discredit the company “ring true.” “This is very much ‘insider’ news and the ethical bar is set incredibly low these days for any major tech firm,” he said. “Despite the impassioned arguments by Microsoft against Google’s alleged astroturf strategy, few will have much interest in hearing them, and likely even less sympathy for either party in the dispute.”
Selon Alan Pelz-Sharpe, fondateur du cabinet d’analystes Deep Analysis, ce partenariat représente une nouvelle étape dans la transformation en cours de Box, qui passe d’un référentiel de fichiers à une plateforme de confiance pour les données non structurées, l’IA et l’automatisation. Les entreprises spécialisées dans l’IA ont besoin de données non structurées pour travailler et apporter de la valeur, et non de données structurées dans des clouds de données tels que DataBricks ou Snowflake.
Enterprise content management (ECM) vendors — not just Box, but also companies such as OpenText, Microsoft and Dropbox — are sitting on “goldmines” of unstructured data, he said, which puts them in the driver’s seat of this year’s rush to add AI into the enterprise tech stack. That doesn’t mean unstructured data is high quality, relevant, well-maintained or accurate. It is early days in which IT teams are mixing generative AI and ECM, and much progress is still to be made. “That’s a big opportunity,” Pelz-Sharpe said. “But it’s also a huge challenge to overcome.”
Alan Pelz-Sharpe, founder of market research firm Deep Analysis, said Google’s complaint against Microsoft highlights the risk of vendor lock-in. While the use of open source software and even cloud computing have attempted to free businesses from their dependence on specific hardware to run particular applications, Pelz-Sharpe said, it has resulted in little success and is still a risk that enterprise business leaders need to be aware of.
Machine processing of documents also carries fundamental implications for the actual structure of documents. Alan Pelz-Sharpe, also from Deep Analysis, notes, “The business information contained in files accounts for a small proportion of the overall file size but typically represents most of the file’s value…Traditional ECM systems were designed for human interaction, but automation, driven by AI, is shifting the balance toward machine processing.”
While Wave 2 is a significant release, Deep Analysis founder Alan Pelz-Sharpe told Reworked, it is as much an acceleration of Microsoft’s marketing efforts due to the slow monetization and widespread doubts about the value and effectiveness of generative AI. Enterprises are pushing back against the unprecedented cost of generative AI, he continued, as it remains hard to justify its value. Moreover, there are deep concerns regarding accuracy, security and compliance. “Wave 2 as such, in theory at least, focuses more on internal data than external data sources. Moreover, the pitch of Agents is specific to job roles, rather than just generic task support, so the hope is this will gain more traction,” Pelz-Sharpe said. “There are certainly some good RPA-style use cases (repetitive and highly predictable tasks) that will benefit here — but beyond that it’s not so clear.”
During the past few years, there has been a lot of talk about citizen developers, which, in the simplest of terms, means that regular business employees can build their software applications without involving specialist IT staff. It should be apparent to readers of KMWorld that information professionals ought to be first in line to become citizen developers. But creating business applications is not a trivial pursuit. Fortunately, hand in hand with the concept of citizen developers come lowand no-code systems that, as the names imply, require no or minimal coding. It’s a great idea that promises to allow those with hands-on understanding of specific business needs to create applications without involving the IT department. Done well, information and knowledge management practitioners can build many simple but practical applications, from routing users to the correct resources to automating repetitive tasks.
