Deep Analysis

💡 The Shift to AI Agents: Prepare for Pay-Per-Use Pricing 💡 The free AI buffet is ending, and metered pricing is on the rise. Companies are moving beyond generative AI assistants like ChatGPT and Co-Pilot to AI agents that can make decisions and perform tasks autonomously. But here’s the catch: you’ll soon be paying for every interaction. Salesforce is leading the charge, with plans to charge $2 per conversation for its new AI agents. The shift toward consumption-based pricing is about to change the landscape for companies relying on AI. 🧠 Key Takeaways: AI agents are more powerful than generative assistants. They don’t just assist—they make decisions and follow workflows. ⚡Prepare for metered costs. Instead of flat fees, every AI-driven interaction could come with a price tag. ⚡Identify where AI agents bring real ROI. Not every use case will justify the cost, so choose wisely. ⚡Budgeting for AI will become more complex. Companies will need to plan for AI costs like they plan for cloud services. Is your organization ready to manage the new economics of AI? The shift from free trials to usage-based pricing is happening fast. This is a quick snippet from We Love Ugly Data Podcast, Series 3, Episode 9. Head over to our YouTube channel to subscribe. #AI #AIagents #Salesforce #genAI #DigitalEconomy #BusinessStrategy

Our door is always open for a briefing if you are a tech vendor working in the world of 'unstructured data.' We seek big and small vendors that add business value and innovate. There are no hoops of fire to jump through to get a briefing :-) Just click on the link below, and we can find a time that works - you will get honest feedback and frequent interruptions, but we think it's worth it, as do countless vendors who have already briefed us. #AR #analystrelations #innovation https://lnkd.in/eCbztdCP

The AI Hype is Real—But So Are the Challenges The AI gold rush isn’t making money—yet. But preparing for AI? That’s a different story. The reality on the ground is clear: enterprises aren’t making big AI investments just yet. System integrators (SIs) and tech vendors report that AI hype is bringing attention—but not revenue. Instead, the real money is in getting organizations AI-ready. Key Takeaways for IT Decision-Makers: -> AI Hype Isn’t Driving Revenue (Yet) – Despite all the excitement, companies are holding off on AI spending. Instead, they’re investing in data readiness. -> System Integrators Are Focused on Cleaning Up Data – Enterprises have tons of data, but much of it is unusable for AI. SIs are making money by helping businesses sort out their messy data. -> Legacy Systems Are a Major Obstacle – Businesses stuck with outdated ECM and ERP systems are facing a choice: modernize or get left behind in the AI era. -> Tech Vendors Need Strong Partner Networks – Companies that are adapting to AI-driven market changes are the ones working closely with their partners. -> AI is a Long Journey, Not a Quick Win – The AI revolution is happening, but it won’t be overnight. Companies that take a strategic, long-term approach will emerge as winners. AI is reshaping the business landscape, but the biggest opportunities today are in preparing for AI—not deploying it just yet. Enterprises that invest in data readiness and strategic modernization will be best positioned for long-term success.

Talk With Us - Vendor Briefings (No, You Don't Need to Be a Client) The IT industry is vast. Our corner of it (unstructured data and business automation; which encompasses aspects of AI, especially Agentic AI) contains hundreds of vendors. We try to talk to as many as possible. (Grab your spot today: https://lnkd.in/eCbztdCP). Why? Simple. The more we know, the better we can guide our clients. These vendor briefings are more like conversations. You won't get through more than 10 minutes with a traditional "deck." Bring your product and company updates, but also bring your knowledge of the industry, what users want today (and tomorrow), and thoughts and opinions. We can read a press release, we don't need that information recited to us. Instead, be prepared for an honest conversation that will enhance how we both understand the industry. We'll talk to you soon! (Here's that link again: https://lnkd.in/eCbztdCP).

Surprising Stats on AI and Unstructured Data Management Unstructured data is the backbone of AI’s potential—and it’s reshaping industries faster than many of us expected. Here are some eye-opening stats from recent research by Deep Analysis and AIIM that might surprise you: 🔍 77% of organizations have AI projects in production or evaluation – AI adoption is accelerating, with businesses moving from experiments to integrating AI into daily operations. This is transforming how unstructured data is managed across sectors. 🔍 Security, access compliance, and performance are top concerns – While “AI hallucinations” grab headlines, 43% of enterprises are more focused on security, while 40% prioritize performance and accuracy. 🔍 Over half of unstructured data is now stored in the cloud (67%) – This data migration trend is reshaping IT infrastructures, but it’s also increasing associated costs for 55% of organizations as they ramp up software investment. 🔍 Enterprise automation (69%) and knowledge management (61%) lead in software investment – As unstructured data grows, organizations are investing heavily in tools that streamline workflows and enhance data accessibility. 🔍 92% of organizations have identified processes AI can improve – AI isn’t just futuristic; it's creating immediate, practical improvements in existing business processes across diverse industries. The race is on to harness unstructured data for meaningful AI insights. Research from Market Momentum Index: AI and Unstructured Data Management, commissioned by AIIM and sponsored by M-Files. Grab your own copy from either of their websites. #AI #GenAI #workflow #unstructureddata #intelligentautomation #contentservices

Unsolicited Advice for IDP vendors: Show more than just invoice processing!  All of us here at Deep Analysis have lost count of demos and products and use cases aimed at invoice processing. We get it – everyone has invoices. Many remain paper-based. It is still a solid revenue opportunity.  All true things.  However, do you want to actually get the attention of analysts/press? • 95% of IDP demos focus on invoice processing, a use case that's decades old • Vendors should highlight more innovative document types and use cases • Example: One vendor impressed by demoing body cam video text extraction for police  Yes, we think that the “meat and potatoes” aspect of technology applications are worth discussing. Specific to IDP, the technology does so much more – you need to show us what you can really do.  Let’s talk. Our metaphorical door is always open to vendors. Our chat can be a one and one meet and greet or evolve over time into a more involved relationships. It all starts with a conversation. Drop us a line below or DM any of us.

Agentic AI is stepping into the spotlight. Also called agent-based AI, this emerging technology builds on the automation revolution started by robotic process automation (RPA). But instead of focusing on repetitive tasks, Agentic AI aims to automate entire decision-heavy processes. Here’s why it matters. From Tasks to Intent RPA was a game-changer, handling repetitive tasks like data entry with ease. Yet, whenever a unique scenario arose, it hit a wall—human intervention was needed. Enter Agentic Process Automation (APA). Backed by Large Action Models (LAMs), APA goes beyond rule-based logic. It evaluates the intent behind tasks, predicts the best next action, and executes it, much like how large language models (LLMs) predict words. Imagine a customer service chat: RPA might automate account balance inquiries, but Agentic AI can reset passwords, update login data, and log issues seamlessly—all while understanding the broader context of the customer’s problem. Opportunities and Risks Agentic AI promises streamlined operations, fewer errors, and lower costs. It could augment roles in decision-making and creativity by automating routine tasks, freeing professionals to focus on complex, high-value work. Yet, challenges loom. Over-reliance on AI, job displacement, and biases in decision-making raise ethical concerns. Who Benefits? Big enterprises with vast datasets are best positioned to leverage this tech, leaving small businesses at risk of falling behind. The real question isn’t just what Agentic AI can do—but what balance we’ll strike between efficiency and the human touch. The future waits for no one. Are you ready for what’s next? This post is from Alan Pelz-Sharpe's regular KMWorld column. The link to the entire full column is in the comments.

Beyond the walled gardens, can business applications really break out and become the ultimate agentic orchestrators? Matt Mullen has thoughts. After a conference season spent absorbing approximately one million agentic software slides (a conservative estimate), a pattern is emerging. Business application vendors are beginning to look beyond their own carefully tended properties toward their neighbours — and that shift provides some useful clues about how agent adoption may actually unfold. We’re in the brief, Thanksgiving-induced lull before the industry resumes its relentless 2025 events cycle. There’s still room for surprises. Oracle used to drop an acquisition a few days before Christmas simply to keep analysts twitchy. And we’ll all be half-watching AWS re:Invent for anything that tries to nudge gravity in our corner of the tech world. A reminder: don’t underestimate CRUD. CRUD is often all we have. One of the more persistent threads this year has been the existential-threat narrative surrounding business applications. Satya Nadella’s early-January comment sparked it, although the subsequent “AI kills SaaS?” excitement came mostly from people conflating terms. It never made much sense, business logic isn’t something you lift and drop between systems, but it didn’t stop the louder voices (including a few CEOs) from speculating about which long-standing totem might be disrupted first. Vendors may dislike the wall garden metaphor, but it holds. Their survival has always relied on controlling the domain: your processes run in their application; your data sits in their infrastructure. As customers moved from on-prem to SaaS — a migration still far from complete — those walls only grew more defined. The first AI arms race was defensive. Everyone needed an assistant to maintain feature parity. The second, built around agents, revealed something more interesting. It depended entirely on the existing automations that form an organization’s business logic. That didn’t erode the walls; it reinforced them. And then, unexpectedly, it provided a vantage point. Instead of external entrants building ladders to scale the walls, the ladders were constructed inside the gardens, to break out, not in. Enter the Action Libraries. Vendors have been refactoring their proven workflows into callable, packaged functions. The logic isn’t moving; it’s being packaged. And once packaged, it doesn’t much matter which trusted agent assembles the plan. Given the heterogeneous reality of enterprise software, this opens the door for a single business application to claim orchestration authority without shifting any data or underlying logic. But a slide deck is not reality. If any trusted agent can assemble workflows from packaged functions, then business applications don’t automatically control the orchestration layer. In this model, trust — not territory — determines who gets to survey the landscape beyond those once-well-defended walls.

The Supply Chain Opportunity in the Age of AI and Automation Before the pandemic, most people never thought about the supply chain. Now, everyone is aware of its importance. From chip shortages to global shipping delays, disruptions have made the supply chain a critical topic. But there’s a bigger story here—one of untapped opportunity. The Supply Chain is a Goldmine for Automation The supply chain generates enormous volumes of documents daily—yet most remain manual and paper-based. This industry is ripe for automation and AI-driven document processing, offering efficiency gains and cost reductions. Tech vendors and startups have finally taken notice and are investing in supply chain solutions. Understanding the Complexity is Key -> The supply chain isn’t a single entity; it’s a network of industries: -> Manufacturing -> Transportation -> Procurement -> Warehouse management -> Distribution Each has unique challenges and requires tailored automation solutions. The Scale of the Document Problem -> In the U.S. alone, the packaging industry is worth $200 billion. ->The largest container ships can carry 24,000+ containers. ->Each container requires ~100 documents (bills of lading, import/export paperwork, certifications, etc.). That’s millions of documents daily—a massive burden and a massive opportunity for automation. The Road Ahead for Tech Vendors The supply chain needs automation, but selling into this space is not easy. Many vendors underestimate the complexity of processes and regulations. Success will require deep industry knowledge, AI-driven solutions, and strategic partnerships. The supply chain industry isn’t just about logistics—it’s about information management. Automating its vast paper trail will be a game-changer. The companies that figure it out stand to win big. Ready to pursue automation in your supply chain? We can help.

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