AI Visionary: Phillip Kingston on Shaping the Future of Work
The Vision Behind AI at AppliedAI
Phillip Kingston, CTO and Co-Founder at AppliedAI, an enterprise artificial intelligence company based in Abu Dhabi, has always been driven by a deeper purpose than just automation. "I became interested in AI because I wanted to solve a deeper challenge than automation: how to scale human judgment," he explains. For Kingston, the potential of AI lies not just in streamlining operations but in scaling expertise.
"Most technologies scale infrastructure yet AI has the potential to scale expertise," he continues. "I realized that if the world could scale not just labor but expertise, we could unlock an entirely new ceiling of human capability."
Kingston highlights his most significant milestone as leading the development of the Opus Large Work Model, the Opus Work Knowledge Graph, and the Opus Data Project. These are AI-powered workflow engines designed to automate complex operations end-to-end, grounded in real organizational logic and continuously improved through real-world performance data.
Addressing Operational Complexity with AI
At the first Dubai edition of /function1, a two-day event bringing together AI industry experts, thought leaders, and business leaders, Kingston shared his insights on the future of AI-driven innovation. He emphasized the need for next-gen business leaders to prioritize combining intelligence, compliance, and scale to unlock true innovation.
AppliedAI focuses on solving the core problem of operational complexity and data growth, which are expanding exponentially while organizational structures still rely on linear human effort. Most AI solutions either break under real-world variability or lack trust in regulated environments. In contrast, AppliedAI encodes business logic and compliance into Opus workflows that continuously improve, delivering 10X outcomes rather than experiments.
Enhancing Human Interaction Through AI
Beyond efficiency, AI-driven tools can also enhance human interactions by removing mundane tasks and allowing space for meaningful conversations. "When AI takes on all the repetitive, transactional work, people finally get to spend their energy on the human parts of work: empathy, incisive problem-solving, and meaningful interaction," says Kingston.
This shift leads to roles evolving from execution to supervision, increasing job satisfaction and creating more connected workforce environments. It fosters a culture where people feel empowered to contribute to shaping how operations evolve.
The Competitive Edge in AI
With many brands offering their own AI assistants, the competitive edge for businesses lies in governance and specialization. "The real competitive edge in enterprise is governance and specialization," Kingston states. Businesses that encode their unique know-how into workflows and enforce auditable constraints will build capabilities to transform cost and productivity.
Leaders must ensure innovation doesn't outrun control by designing compliance into the system from day one. The winners will be those who innovate with discipline, as trust for production workloads becomes the new moat.
Common Misunderstandings About AI Adoption
One of the biggest misunderstandings about AI adoption is thinking you can plug in AI to 'as-is' processes without redesigning how work happens. "That's why so many pilots fail to scale," Kingston explains. Successful AI adoption begins with clarity, structure, and intentional design for an AI-first world.
AppliedAI helps organizations generate AI-first workflows from intent and objectives, then run them at scale. This approach ensures that AI is not just an add-on but a fundamental part of the operational framework.
Fostering Innovation and Workplace Culture
Kingston has witnessed AI-driven operational structures uncover more innovative ideas and better workplace cultures. When systems handle execution and humans guide complexity and improvement, a different culture emerges. "We're seeing AI become the 'maker' and humans become the 'checker'," he notes.
This shift empowers people to innovate, as they are no longer buried in routine tasks. Expertise becomes shared, and everyone contributes to shaping how the operation evolves, resulting in a workplace defined by continuous improvement and collective intelligence.
Future Trends in AI
Looking ahead, Kingston anticipates that AI will move from helping with tasks to orchestrating entire workflows through multi-agent collaboration. Enterprises will increasingly buy results rather than software, as automation will be expected to operate with built-in compliance and accountability.
The gap between companies adopting supervised automation and those relying purely on human scale will become economically irreversible. Businesses that combine intelligence, compliance, and scale will define the next global productivity frontier.
