Editorial
McDonald’s a few years ago decided to compete with Starbucks, a decision that puzzled many business strategists, including me.
Starbucks built its brand around differentiated coffee drinks, an inviting workspace and premium customer experience. In contrast, McDonald's thrived on speed, efficiency and affordability — attributes that seemed at odds with Starbucks' value proposition. Yet McDonald's saw an opportunity: a segment of Starbucks' market that did not care about customer experience or the remote-work-friendly atmosphere but was willing to pay for premium coffee. The strategy made sense on paper, but execution in the end proved challenging, as it required shifting customer perceptions and changing operational realities.
Now, I am experiencing a sense of strategic déjà vu. Agentic AI has become an obsession within the software industry, with every major player scrambling to establish a winning agentic AI strategy. The rapid adoption of AI agents — software that can autonomously plan, execute tasks and adapt to complex environments — has sparked a race to redefine the future of software. But as with any transformative technology, this change raises more questions than answers.
How will agentic AI reshape the software industry? Will it create entirely new market segments, or will it simply disrupt existing ones? More importantly, how will this shift alter competitive dynamics?
History shows that when a technology wave emerges, some companies position themselves as leaders while others struggle to find relevance. So, who will win this race, and what key technological components will define early success? Without question, the companies that succeed will not just bolt agentic AI onto existing products — they’ll rethink their software from the ground up. Winners will master the orchestration of intelligent agents, ensure seamless integration into enterprise workflows and solve real-world problems more effectively than traditional approaches including traditional machine learning (ML). The question is not just who adopts agentic AI, but who creates a way to leverage it in a way that creates sustainable competitive advantage.
Software’s Great Convergence
The software industry has long been defined by distinct market segments. These included applications, productivity tools, data systems, AI and data modeling and low-code/no-code workflows. Each of these mostly operated within its own boundaries, serving specific needs and customer bases. But that separation will erode as agentic AI emerges as a disruptive force.
Agentic AI has put historical segments on a collision course. The core features of applications, automation and AI-driven decision-making are blending together, and the companies that succeed will master the integration of these once-separate capabilities. The real question is what the industry will look like once the dust settles. If history is any guide, the rigid market categories of today will give way to a new landscape defined by two primary functions: applications that turn data into action and data that fuels business productivity.
This shift is already happening. Companies like Domo have demonstrated AI agents that can reshape customer service within Salesforce and streamline resume sorting — tasks that belong to tightly defined and separate markets. As agentic AI dissolves traditional software boundaries, the winners will be those that rethink their approach, seamlessly integrating AI-driven automation with data-rich insights to create entirely new value propositions.
Related Article: The AI Agent Explosion: Unexpected Challenges Just Over the Horizon
Rethinking Advantage in a Changing Market
The winners in agentic AI will assemble a critical mix of technologies and strategically leverage integrations based on purpose. These core technologies include a large language model (LLM), instructions (what to do), knowledge (how to do it), data and tools to implement tasks. The key differentiator lies in how these components are combined to create actionable, intelligent systems.
Process-oriented application vendors and low-code/no-code platforms have an early advantage in the realm of instructions. Industries such as customer service and IT service management have spent years refining process workflows for human workers. By connecting these institutional process capabilities and structured and unstructured data to an LLM — along with the ability to act — organizations can dramatically transform how tasks are performed. The result is a shift from human-dependent workflows to AI-driven automation, accelerating efficiency and reducing manual effort.
Market advantage will favor those that enable work arbitrage, automate actions and accelerate knowledge discovery. Initially, companies with well-defined workflows will benefit most, as structured processes lend themselves more easily to AI automation. Over time, new opportunities will arise, favoring low-code/no-code platforms that can rapidly define and adapt workflows. On the data and knowledge side, productivity tools like Slack and Teams, as well as business-oriented data marketplaces, will gain an edge by facilitating seamless knowledge sharing and reducing workflow friction — such as allocating data without requiring a ticketing system.
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Given these dynamics, early winners will include companies like Salesforce and ServiceNow, along with other application vendors that embed agentic AI into their ecosystems. Low-code/no-code platforms will also thrive by enabling businesses to define new workflows on demand. As Howard Dresner of Dresner Advisory Services observed, “We are conducting our first research of agentic AI, but we are seeing our clients jump on this quickly. No one can predict exactly how this will reform the market. However, it will be different. We see a huge opportunity for agents to transform businesses and how people work. The winners, however, will focus on augmenting rather than replacing people. They will also shift from an application-centric approach to a data-centric one.”
The Bottom Line on Agentic AI
The rise of agentic AI is more than just another tech trend — it is a fundamental reshaping of the software industry. As intelligent agents become more capable of automating processes, making decisions and executing tasks, the traditional boundaries between software segments are dissolving. What once were distinct markets are now converging into a new, dynamic competitive landscape.
The companies that win in this transformation will not simply add AI agents as a feature but will fundamentally rethink how their software operates. Success will depend on mastering a critical mix of technologies. Those who already possess structured workflows are positioned to move quickly, while low-code/no-code platforms will enable new workflow creation and adaptation. Meanwhile, companies with strong knowledge-sharing ecosystems will benefit from AI-driven collaboration and decision-making.
The market is shifting from fragmented software categories to two core pillars: applications that turn data into action and data that fuels productivity. In this new reality, competitive advantage will belong to those who reduce friction, enable automation and enhance knowledge discovery at scale. As Dresner noted, "No one can predict exactly how this will reformat the market. However, it will be different." The only certainty is that companies must act now to define their role in the agentic AI era — or risk being left behind.
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