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AI Changes Everything: Zafin’s Move to Run-Time Design and Personalized Experiences. AI is the new OS.

By: Charbel Safadi, Branavan Selvasingham, Melissa Valdez

With support from Zafin Copilot, powered by generative AI on Azure
June 27, 2024
10 min read

At Zafin, we believe Generative AI is poised to become the operating system of the future, an omnipresent force that underpins every digital interaction. In this future, the static user interfaces and predetermined flows we’ve grown accustomed to will give way to dynamic, personalized experiences crafted by AI in real-time, tailored to each user’s request and preferences.

In this article, we will explore Zafin’s perspective on generative AI and how it will redefine the way we interact with technology, design our workflows, and envision the future of digital enterprises. This is not just an evolution of the digital experience; it’s an opportunity to fundamentally reinvent how we interact with our data and our customers.

Generative AI as the operating system of the future

Generative AI is rapidly positioning itself as the operating system of the future, a foundational layer upon which the next generation of technologies will be built. Much like an operating system that manages a computer’s basic functions and facilitates the creation and execution of software applications, generative AI will orchestrate complex tasks, automate decision-making processes, and generate content across various domains.

Its ability to iteratively improve, adapt, and produce outcomes beyond the scope of predefined programming makes it an indispensable tool for innovation. As generative AI continues to
evolve, it will become the bedrock of digital ecosystems, enabling businesses to operate with unprecedented agility and creativity.

The implications of generative AI for businesses and consumers are profound. For businesses, it means a shift towards more dynamic and responsive operational models, where AI-driven systems can anticipate market changes, optimize workflows, and personalize customer interactions at scale. Consumers, on the other hand, will benefit from more intuitive and tailored experiences, as generative AI learns to understand and predict individual preferences and behaviours. This symbiotic relationship between generative AI and its users promises not only to enhance efficiency and productivity but also to redefine the very nature of how services are conceived and delivered.

Orchestrators of the Generative AI era

In the Generative AI Era, the landscape of business is being reshaped by those who can adeptly navigate the complexities of AI-driven processes. Companies that emerge as leaders will be the ones that embrace generative AI and excel in efficiently routing workflows through it. This efficiency isn’t just about speed; it’s about cost-effectiveness and precision. In identifying the most economical paths for AI to accomplish tasks, these organizations optimize operations, reduce overhead, and unlock the ability to deliver services at a scale and speed previously unattainable.

Orchestrators play a pivotal role in this new era, acting as the strategic conductors of generative AI resources. They are the architects of the AI workflow, ensuring that the right tasks are matched with the most suitable solutions. Effective orchestration involves a deep understanding of the capabilities of various AI models, the ability to integrate them seamlessly into existing systems, and the foresight to anticipate and adapt to the evolving needs of the business. Organizations must also be adept in managing the delicate balance between human expertise and AI automation, ensuring that they amplify each other’s strengths. A well-orchestrated digital ecosystem accelerates the organization’s capacity for innovation via action-oriented agents and unlocks new possibilities for customer engagement.

We asked an executive from a large, leading North American bank (also one of our customers), to share their thoughts here, and this is what they said:

“Just like any transformation, there’s a need to rewire aspects of your organization as you look to compete in the age of AI and automation:
  1. A horizontal data strategy, a solid cloud formation, a micro-services and open systems architecture, and hollowed-out cores are paramount to making AI successful and building an ecosystem around it.
  2. Creating value and services at scale using personalization techniques is key, but so is capturing it.
  3. Evaluating and reviewing your operational model is critical and is where most of the work lies. There’s a big change management aspect and an opportunity to partner closely with HR and leaders as we ready the organization for this transformation.”

The rise of action-oriented agents

A key function of generative AI orchestrators is disambiguating tasks and routing them to the appropriate action-oriented agents. These agents are designed to not only process information but to take decisive actions based on that information. They differ from their earlier, deterministic counterparts in their ability to autonomously execute tasks, make recommendations, and interact with other systems. Action-oriented agents embody the fundamental shift from passive data analysis to proactive problem-solving, marking a significant milestone in the evolution of AI for enterprise.

The introduction of these action agents presents a new challenge for adaptive authorization within the enterprise. Traditional access controls are not equipped to handle the dynamic and complex decision-making capabilities of action-oriented agents. There is a pressing need for a more flexible and responsive authorization framework that can accommodate the autonomy of these agents while maintaining security and governance. This is where the concept of intent-level entitlements comes into play.

Intent-level entitlements are designed to grant permissions based on the requesting user’s permissions and their request’s intention, rather than the agent’s action itself. This approach requires a sophisticated understanding of the user’s authorizations across enterprise systems, the agent’s capabilities, and the context in which it operates. In addition, it’s critical that the agent’s available actions are aligned with the enterprise’s objectives and risk appetite. Structuring such entitlements will involve a combination of policy definition, real-time monitoring, and adaptive controls that can evolve with the agent’s learning and the enterprise’s changing needs.

The end of pre-determined user flows

This new reality marks the end of pre-determined user flows and static digital designs, since it introduces a level of personalization and adaptability that was previously unachievable. Traditional user flows, which guide users through a fixed sequence of steps, are becoming obsolete in the face of the AI action agents that can dynamically generate user experiences. Generative AI can assess the context of each user interaction in real-time and create custom user interfaces and visualizations that cater specifically to the individual’s needs and preferences. This means that two users could perform the same function within an application and have entirely different experiences, each optimized for their unique way of interacting with the system.

This shift towards on-demand customization places a premium on analytical, visualization, and signalling functionalities. Well-orchestrated generative AI tools can prioritize the most relevant next steps, simplify complex information, and even anticipate user needs before they are explicitly stated. For businesses, this translates to higher engagement, improved user satisfaction, and the ability to deliver complex services with ease. For consumers, it means a more intuitive and frictionless digital experience that feels as though it was designed just for them. As we move forward, the ability of generative AI to create these bespoke experiences will become a key differentiator in the digital marketplace, setting a new standard for user-centric design.

An example at Zafin

Jake is a product director in a large bank.

An agent-initiated action sequence alerts the user of key information.
Actions taken by an agent based on a user’s request to help offload redundant user tasks
Advanced data analysis from multiple sources helps create novel insights, leading to better products.
Multi-modal experiences help create a deeper and more nuanced understanding.
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Conclusion

The transformative power of generative AI is undeniable. From the rise of action-oriented agents to the reimagining of user interfaces, generative AI is a paradigm shift that will redefine the way we interact with our customers, our data, and each other.

Businesses that harness the potential of generative AI via efficient orchestration will find themselves at the forefront of innovation, able to navigate the complexities of the digital world with unprecedented agility. Consumers will enjoy more personalized, intuitive experiences as static user flows give way to dynamic, real-time generated interactions. As we embrace the possibilities afforded by generative technologies, we must also adapt to the evolving landscape of authorization and security.
Future digital experiences are not pre-determined; they are generated in real time. The winning organizations will be those who embrace the operating system of the future – a well-orchestrated AI system powered by autonomous action agents and truly customized user experiences.

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