Managing Director Americas
AI is evolving at a breakneck pace, with new players and innovations reshaping the landscape. Microsoft is now partnering with DeepSeek, a Chinese firm, beyond OpenAI. Mistral’s ‘Le Chat’ is gaining traction in Europe, while Elon Musk’s xAI is making rapid progress. Meanwhile, OpenAI pushes forward with GPT-4.5 and GPT-5, even as concerns arise about its competitive edge.
Not to mention the release of many new agents and autonomous tools (like Manus) and more agentic deep research tools etc. OpenAI’s new plan for $20k/month agents for PhD-level research.
All this leaves business leaders facing a crucial question: What AI advancements should they prepare for? Here are four key trends set to redefine industries in the near future.
AI will integrate text, images, audio, and video, creating human-like interactions.
As AI becomes more perceptive, trust and privacy concerns will skyrocket. Imagine AI hearing every office conversation, analyzing grocery store behaviors, and even detecting emotions. It will eventually be able to understand (and manipulate) human emotions better than humans.
The trajectory of AI points towards the rise of autonomous agents by 2026. These self-governing systems will execute intricate tasks without human intervention, ranging from managing supply chains to optimizing financial portfolios.
Organizations need to establish robust governance frameworks to oversee AI agents, ensuring ethical operations, compliance with regulations, and alignment with corporate values.
Traditional AI models, once static after being deployed, are evolving into dynamic entities capable of continuous learning. AI systems will autonomously update their knowledge bases, adapting to new information and changing environments in real-time.
Continuous Learning requires more vigilant monitoring to prevent biases and errors. Corporations will need to invest in infrastructure that supports real-time data processing and model validation.
The AI revolution is underpinned by advancements in computational technologies:
Efficient AI models: New models will be optimized for performance while reducing energy use.
Edge Computing: Processing power is moving closer to data sources and external devices (like your phone, or a vending machine, for example), enabling real-time analytics and reducing latency. This decentralization enhances data security and operational resilience – and also enables AI to enter spaces that don’t have connectivity.
Quantum Computing: By the late 2020s, breakthroughs in quantum computing could exponentially increase AI processing capabilities, solving complex problems previously deemed impossible.
Staying up-to-date with these technological developments and investing in scalable, future-proof infrastructure will be critical for sustaining AI-driven growth.
Rather than chasing every new model, corporate leaders should:
The AI landscape is evolving too fast for anyone to keep up with every new model. The real challenge isn’t just tracking innovation—it’s knowing which advancements matter and how they solve real-world problems. Step back from the hype and focus on what truly counts: making AI work for humans, not the other way around.
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Managing Director, BOI (Board of Innovation)
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At the intersection of strategy, emerging technology and innovation Geoff leads our Americas team to craft AI strategy and build innovative AI-powered solutions. With equal amounts of optimism and skepticism, there’s nothing Geoff loves more than a new problem to solve.
