Is BizOps the best way to scale AI?

In this article let’s delve deep into why traditional monolithic enterprise SaaS platforms like CRMs and ERPs are becoming increasingly ill-suited for decentralized and federated business models—and how BizOps is paving the way for a more agile, flexible, and intelligent approach to scaling AI in enterprise operations.

Breaking Free from Monolithic SaaS: The Problem with CRMs and ERPs

Most enterprise software today—think CRMs, ERPs, and other large-scale SaaS platforms—are built to centralize data and streamline core operations within a single ecosystem. While this worked well in the past, these monolithic platforms aren’t designed for decentralized or federated operations. They operate as rigid, centralized hubs, imposing a one-size-fits-all model that can’t easily adapt to localized needs or autonomous team structures.

The challenge with these systems is twofold. First, the cost of scaling them to meet the needs of dynamic and diverse teams is astronomical. As companies grow, they often find themselves investing heavily in customizations and extensions, only to discover that their enterprise software has essentially become a glorified data collection mechanism. This approach stifles flexibility and impedes the ability to make real-time, data-driven decisions at the local level.

Solution: BizOps, A Microservice-Like Approach to Enterprise Operations

BizOps offers a pathway to move away from these monolithic architectures towards a more decentralized, microservice-like model of operations. By embracing BizOps, organizations can achieve a state where various business teams function autonomously and with agility but remain interconnected. This enables localized decision-making, greater operational flexibility, and improved agility across the board.

Instead of relying on a single platform, BizOps encourages companies to adopt a modular and composable approach to technology. Each department or business unit can deploy tools and processes that best suit their needs while still adhering to overarching organizational standards. This model enables organizations to dynamically respond to market changes, scale operations with ease, and deploy AI-driven insights where they matter most.

Scaling Next Best Action (NBA) Across the Organization

One of the most powerful outcomes of BizOps is the ability to scale the Next Best Action (NBA) approach beyond just sales or marketing, integrating it into every facet of the organization. NBA combines AI-driven insights with business objectives to guide decision-making in real time. By scaling NBA across the entire organization, companies can transform how they respond to customer needs, optimize workflows, and allocate resources.

Traditionally, NBA has been confined to specific use cases, like CRM-driven sales recommendations. But with a decentralized BizOps framework, NBA can be applied to virtually any operational domain, from supply chain management to customer service. This scalability is critical for organizations that want to move beyond siloed, reactive AI use cases and embrace proactive, cross-functional intelligence.

AI Agents and NBA: The Key to Unlocking AI Value

The next step in scaling AI within an organization is to combine AI agents with NBA to automate and optimize decision-making at scale. AI agents, when paired with NBA, can autonomously evaluate options, make recommendations, and execute tasks without human intervention. This creates a closed-loop system where AI not only generates insights but also acts on them in real-time, making BizOps-driven organizations truly intelligent and responsive.

In this setup, AI agents can support in handling a variety of tasks across the organization, ensuring that every action taken aligns with business objectives. The result is an organization where AI is seamlessly integrated into day-to-day operations, driving value at every touchpoint.

Enabling Human-AI Collaboration with BizOps

BizOps is also the best way to deploy AI agents into operations and unlock new value from combining them with human operators. While AI can handle tasks that require speed, accuracy, and data processing, humans bring creativity, strategic thinking, and nuanced judgment. By structuring operations around BizOps principles, organizations can maximize the strengths of both AI and human agents. This hybrid model promotes intelligent decision-making, with AI handling repetitive tasks and humans focusing on higher-value, strategic activities.

Conclusion

As companies navigate the challenges of digital transformation, the limitations of monolithic enterprise SaaS systems become increasingly apparent. BizOps offers a viable alternative, enabling organizations to operate more like agile microservices than rigid, centralized entities. By leveraging AI-driven NBA, deploying autonomous AI agents, and fostering human-AI collaboration, companies can truly scale the value of AI, creating a responsive, decentralized, and intelligent enterprise.

In this new world, BizOps isn’t just a way to improve operational efficiency—it’s a strategic enabler of long-term growth and innovation. By adopting a decentralized, BizOps-driven approach to scaling AI, companies can unlock new opportunities, meet the evolving needs of their customers, and remain competitive in an increasingly complex and dynamic business landscape.