Automation in SaaS Services

Over the past few weeks, I’ve spoken with several entrepreneurs who are developing all-in-one, AI-powered vertical SaaS applications and making significant progress. In contrast, the previous generation of SaaS companies typically consisted of horizontal platforms that excelled in one market segment, such as marketing automation or sales engagement. These products were comprehensive, serving a wide range of industries. Over time, many of these applications moved upmarket, focusing on mid-market and enterprise clients. In addition to horizontal players, numerous vertical SaaS applications have emerged over the last two decades. These typically followed a playbook of targeting small to midsize businesses in specific segments before gradually moving upmarket. They focused on delivering the most valuable features for their target audience while avoiding overly broad functionality. With the rise of AI-powered software development, including low-code platforms and vibe coding, robust cloud computing resources, and mature open-source ecosystems, building large-scale software quickly has never been easier. As a result, entrepreneurs are now creating AI-powered vertical SaaS products that combine the functionality of multiple horizontal tools into a single, purpose-built solution for specific industries. Instead of small business owners needing separate tools for their website, social media, marketing automation, CRM, and sales engagement, a single system now provides everything they need, tailored to their vertical. These solutions are offered at a significantly lower price point with greater ease of use. Moreover, because these products are directly tied to revenue through lead generation, proposals, and new business, their ROI is clear. My recommendation to entrepreneurs is to identify a vertical they or a colleague know intimately and consider building a comprehensive application that replaces multiple existing tools for that target customer. By leveraging AI, cloud infrastructure, and open-source technologies, they can deliver a fully integrated solution at a fraction of the cost.

For the last 20 years, SaaS has been about digitalization of work. CRMs, HR systems, ticketing tools, all built as systems of record: structured databases with forms and workflows on top. They gave companies visibility and control, but also created friction. Most real work still happens elsewhere: in meetings, emails, Slack, and documents. SaaS tools sit on the sidelines, waiting for users to come back and log what happened. Useful for managers, painful for everyone else. AI flips that model. Instead of forcing people to enter data, it can infer structure from natural work, conversation, text, intent. The software adapts to people, not the other way around. That shift is giving rise to a new layer in the enterprise stack. At the bottom, systems of record hold structured data. Above them, systems of engagement—chat, email, meetings—where people actually work. And now, in between, systems of intelligence: the AI layer that observes, understands, and acts. This layer captures unstructured signals from engagement tools, turns them into structured knowledge, and triggers actions in record systems, all with supervised autonomy. AI proposes, people approve. Every action is transparent, contextual, and traceable. That’s the architecture shift: - Work stays where people naturally do it. - Data stays complete and reliable. - AI handles the translation layer in between. Adding AI copilots to old SaaS tools won’t get us there. Those systems were built for manual data entry, not probabilistic reasoning or learning from outcomes. You can’t bolt intelligence onto a rigid schema. The next generation of products will be AI-native, built around continuous interpretation, context graphs, and human-guided autonomy. That’s what we’re building with Actioner. It connects to engagement tools like email, and meetings, and to systems of record like CRMs or ticketing platforms. It captures real work as it happens, maps it into a graph of companies, people, and interactions, and surfaces suggested actions through an interface where users stay in control. Actioner doesn’t force new workflows. It orchestrates work around people. The last generation of SaaS digitized work. The next generation will understand it, and act on it. That’s the promise of systems of intelligence.

AI isn’t about replacing people. It’s about replacing clicks. We buy SaaS products here at DroneDeploy, probably even more than our customers. For two decades most SaaS products have been aiming for automation…but not really delivering it. Forms became digital. Inspections became digital. Submittals, RFIs, punch lists – all digitized. But under the hood, the workflows stayed the same: people still logging in, filling out forms, just clicking instead of writing. I read Collin Stewart's latest blog (linked in comments) and agree that SaaS at its core is just a database with a UI and some business logic. What’s finally changing is the layer above it: AI agents that don’t just store and display information, but actually do the work in the background. So what's a real world example?  Progress tracking to get ahead of trade stacking still requires someone walking the site, capturing phone photos, typing updates into a field app, and/or manually highlighting a drawing. That’s the grunt work – the schlep, as Collin puts it – that AI can eliminate. And it’s exactly where DroneDeploy is focused. We’re building agents that operate inside a visual twin of your site, doing the schlep work that no one actually wants to do. Progress AI removes the clicks and taps to manually highlight a drawing, then identifies trade stacking automatically. Safety AI removes the clicks and taps you would need to identify 95% of visible OSHA Safety risks on your site, then lets you decide what's worth following up. We've got least one other AI agent in the works that does work in the background in your visual twin. No forms, extra apps or lag time. It’s not jobs AI and agents are eliminating. It’s clicks.

GenAI is not just enhancing SaaS—it’s redefining it! This insightful article from HBR highlights how AI agents could bypass traditional SaaS UIs, shifting value from tools to outcomes and orchestration, from systems of workflow to systems of work. Key takeaways: - SaaS is becoming an execution layer for intelligent agents, not a UI for workflows - Vertical AI agents will reshape how teams work across finance, IT, ops, and more - The future of SaaS may be “headless”, with agents using APIs directly - Competitive advantage will come from data readiness, workflow design, and AI-first integration strategy - As orgs, we need to move now, rethinking how we adopt tools, designing for AI-native workflows, and measuring success by impact, not logins. Example of moving from systems of workflow to systems of work - Today, Expense reporting means form-filling, dropdowns, and approval chains with each step slowing you down. - Tomorrow, Snap a receipt, and AI does the rest, extracts, validates, routes, approves, and pays all without a single manual click. This shift is already underway. We need to rethink our architecture, unlock value through AI, and lead the shift from tools to intelligence. #FutureOfWork #DigitalWorkplaceExperience #EnterpriseAI #AgenticAI https://lnkd.in/ghiyrxXV