What Got Us Here Won’t Get Us There: The Shift from SaaS to AI

What Got Us Here Won’t Get Us There: The Shift from SaaS to AI

AI Isn’t Just Disrupting Industries—It’s Disrupting the Software That Transformed Them

In 2011, Marc Andreessen famously said, “Software is eating the world.” He was right. The 2010s became a decade of digital transformation, where enterprises invested heavily in software systems—ERP, CRM, HCM—to keep pace with disruptors and modernize internal workflows.

But now, we’re entering a new chapter.

I’ve spent over two decades in tech and sales—helping clients navigate platform shifts, modernization projects, and now, the generative AI frontier. What I’m seeing today is bigger than digital transformation. It’s a seismic shift: AI isn’t just disrupting industries—it’s replacing the very systems that fueled the last wave of progress.

Even Microsoft CEO Satya Nadella, whose enterprise stack powers global business, has warned that the traditional software paradigm is being rewritten. This isn’t hype—it’s happening. And for enterprise leaders, it’s both a challenge and a once-in-a-generation opportunity.


From Workflows to Work: A Big Shift with Bigger Implications

Most enterprise software—Salesforce, Workday, SAP—treats organizations as systems of workflows. Think of it as flowcharts and forms. A workflow gets mapped, built, and baked into the software. To get something done, users have to follow the steps: input data, click through fields, push it to the next person.

That model worked—for a while. But it’s built around structure, not outcomes.

Generative AI flips the script. It enables what I call systems of work—platforms that are goal-oriented and adaptive, not rigid and pre-defined. These systems don’t start with a mapped-out process; they start with the job to be done. They use data signals (structured and unstructured) to figure out the optimal path forward in real time.

Imagine telling your system: “Onboard Jane Doe.” It knows what that means. It pulls the offer letter template, schedules onboarding, sets up payroll and benefits, and provisions her laptop—across multiple back-end systems—without a human chasing down every step.

This is where enterprise software is headed: from manual steps to intelligent orchestration.


Why It Matters: Workflow Software vs. Generative AI Systems

Traditional Workflow Software 🔹 Sequential: Tasks are ordered and rigid 🔹 Explicit: Everything must be predefined 🔹 Expert-dependent: Users need to know the software 🔹 Expensive to change: Redesigning workflows takes months

Generative AI Systems 🔹 Fluid: The process adapts to the goal 🔹 Conversational: Interactions happen in natural language 🔹 Learning: The system improves with every use 🔹 Outcome-focused: Users just ask, and it executes

In a sales context—where I live every day—AI can analyze call transcripts, emails, and CRM notes, then update deal status, draft follow-ups, or forecast revenue—all without a rep clicking 47 times in Salesforce. (Yes, I’ve counted.)


This Isn’t Theoretical. It’s Already Happening.

Here’s what some early movers are doing:

  • Klarna is replacing Salesforce and Workday with custom AI tools that sit on top of a unified enterprise graph.
  • Siemens engineers are ditching ERP systems in favor of conversational AI bots that interact with their product lifecycle systems.
  • JP Morgan is giving research analysts AI tools that scan financial history and draft near-complete reports.
  • Hitachi used an AI agent platform to boost HR efficiency by 70%—across 120,000 employees in just eight weeks.

And these aren’t just pilots. We’re talking enterprise-wide rollouts, with real ROI and momentum.


So, What Should Leaders Do?

I talk to CIOs, COOs, and product heads every week. They all feel the shift—but many are unsure where to start. Here’s my playbook:

1. Governance Comes First

Build trust in the AI system from Day One. Think data quality, audit trails, bias mitigation, and clear handoffs between AI and human decision-makers.

2. Prepare Your People

Workflow-heavy roles—HR ops, IT admin, finance processors—are going to change. Upskill them. Move them closer to strategy, innovation, and customer value.

3. Design for the New Frontier

  • Prioritize interoperability. Your AI won’t replace everything overnight—so make sure it can work with your existing systems.
  • Rethink UX. Ditch dropdowns. Embrace natural language and voice interfaces.
  • Build adoption paths. Not everyone’s ready for fully autonomous agents. Offer middle-ground options.
  • Focus on outcomes, not just workflows. Let the AI figure out the path.


Closing Thought

We’re standing at the edge of a profound change in how work gets done. Just as software ate the world 15 years ago, AI is now eating the software.

The question isn’t whether this is coming—it’s whether your team will lead the charge or get left reacting to it.

At Code Éxitos, we’re already helping clients reimagine their systems and implement agent-based solutions that replace friction with flow.

If you're wondering how to make the leap from exploration to execution, I’m always up for a real conversation.

Let’s turn disruption into advantage—before someone else does.

~ Jason Lukas Competitive former athlete turned sales strategist. Helping organizations simplify complex software challenges and drive outcomes with pleasant persistence.

This is a fascinating perspective on the evolution of AI in the business landscape. The shift from just adding software to focusing on smarter work is crucial. As companies embrace this change, what do you think will be the biggest challenge for leaders in adapting to these new systems?

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Tyler Z. Khalikyar, PMP, CSM, CF-APMP

Experienced Sales Evangelist & Business Development Leader | Structures & Secures Complex Enterprise-Wide Deals >$50M in TCV | AI Enthusiast | Relationship Builder | Closer

2mo

Absolutely compelling take, Jason Lukas. The shift you describe isn't just technological—it's philosophical. As AI begins to decide and do, it raises a deeper question: what becomes of human agency in the enterprise? When systems optimize outcomes automatically, who ensures the outcomes align with our intent and values? We’re not just redesigning workflows—we’re redefining responsibility. Appreciate you sparking this line of thought.

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Jason, I think this is thought provoking and reflects what IS actually happening. This big thing for me is that with AI, software SHOULD finally become easier and more intuitive in the years to come. That will be great ... Whan that happens.

Mihretu Desalegn

Deputy Commissioner at Addis Ababa FDRMC, Technology and Engineering Sector Head | CC | Cybersecurity | Electronic Security

2mo

Definitely worth reading, very insightful.

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Fadi Khoury

Unlocking Human Potential to Drive Innovation and Growth

2mo

Jason, this is a sharp and timely take on the shift from SaaS to AI-driven systems. The move from rigid workflows to adaptive, outcome-focused platforms is spot on, and a change that’s reshaping how we think about software, delivery, and impact. I especially appreciate your focus on governance, skills, and the need for a product mindset to navigate this transformation effectively. Great piece!

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