Aidan Gomez, CEO and cofounder of enterprise AI company Cohere, has outlined his vision for the next phase of artificial intelligence development, which he calls “AI 2.0.” In a recent LinkedIn post, Gomez predicted that 2024 and beyond will mark a shift from generic large language models (LLMs) to highly customized, end-to-end AI solutions tailored to specific business objectives.
According to Gomez, while 2023 was characterized by companies adopting AI to remain competitive, the coming year will focus on customization and optimization. “The next phase of development will move beyond generic LLMs towards tuned and highly optimized end-to-end solutions that address the specific objectives of a business,” he wrote. This transformation will “accelerate adoption, value creation, and will help fundamentally transform how businesses operate,” ultimately leading to a future where “every company will be an AI company.”
Cohere’s Strategic Partnerships
Cohere has already begun implementing this vision through major partnerships with industry leaders. The company has collaborated with Oracle to build customized technology and tailor AI models that power dozens of production AI features across NetSuite and Fusion Apps, with plans to expand to hundreds of features. For Japanese IT giant Fujitsu, Cohere developed Takane, a specialized model designed specifically to excel in Japanese language processing.
In June 2023, Cohere partnered with global management consulting firm McKinsey & Company to develop customized generative AI solutions for McKinsey’s clients. Gomez previously told Business Insider that this work is helping the startup “build trust” among more organizations.
Smaller, More Efficient Models
To meet diverse client needs, Gomez has advocated for smaller, more efficient AI models rather than massive LLMs. He argues these models are more cost-effective and give smaller startups a competitive chance against established AI giants.
However, major players are also entering the customization space. OpenAI recently previewed during its “Shipmas” campaign an advancement allowing users to fine-tune their o1 model—their most advanced AI system—on custom datasets. This technology, set for public release in 2024, has already been deployed with partners like Thomson Reuters for specialized legal tools and Lawrence Berkeley National Laboratory for genetic disease identification models.
Key Quotes
The next phase of development will move beyond generic LLMs towards tuned and highly optimized end-to-end solutions that address the specific objectives of a business.
Aidan Gomez, CEO of Cohere, outlined his vision for what he calls ‘AI 2.0’ in a LinkedIn post, emphasizing the shift from generic AI models to customized business solutions tailored to specific organizational needs.
AI 2.0 will accelerate adoption, value creation, and will help fundamentally transform how businesses operate. Every company will be an AI company.
Gomez’s bold prediction suggests that AI customization will become so integral to business operations that AI integration will be universal across all industries, similar to how internet connectivity became essential for all businesses.
With Oracle, we’ve built customized technology and tailored our AI models to power dozens (soon, hundreds) of production AI features across Netsuite and Fusion Apps.
Gomez highlighted Cohere’s partnership with Oracle as a concrete example of the customization trend already in action, demonstrating how enterprise software is being enhanced with tailored AI capabilities at scale.
Our Take
Gomez’s vision represents a maturation of the AI industry from hype to practical implementation. The “AI 2.0” concept acknowledges that generic models, while impressive, often fail to address specific business workflows and industry requirements. This shift toward customization is inevitable—just as websites evolved from generic templates to sophisticated, brand-specific experiences, AI must follow the same path.
What’s particularly interesting is the tension between Cohere’s smaller-model approach and OpenAI’s strategy of making their massive o1 model customizable. This represents two competing philosophies: purpose-built efficiency versus adaptable power. The winner may depend on use cases—some applications may benefit from lightweight, specialized models, while others require the reasoning capabilities of larger systems. Ultimately, the market will likely support both approaches, with businesses choosing based on their specific needs, budgets, and technical capabilities. The real question is whether smaller AI companies can maintain their competitive edge as giants like OpenAI add customization capabilities.
Why This Matters
Gomez’s prediction signals a critical evolution in enterprise AI adoption, moving from experimentation to practical, customized implementation. This shift has profound implications for businesses of all sizes. As AI transitions from generic tools to specialized solutions, companies will need to invest in tailored systems that address their unique operational challenges rather than relying on one-size-fits-all models.
The emphasis on smaller, efficient models could democratize AI development, allowing startups and mid-sized companies to compete with tech giants without requiring massive computational resources. This could accelerate innovation across industries and reduce the concentration of AI power among a few large players.
However, OpenAI’s move into customization shows that established players aren’t ceding this territory. The competition between specialized AI companies like Cohere and generalist giants like OpenAI will shape how businesses access and implement AI technology. For enterprises, this means more options but also more complex decisions about which platforms and partners to choose. The prediction that “every company will be an AI company” suggests AI integration will become as fundamental as having a website or email system, fundamentally transforming business operations across all sectors.
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Source: https://www.businessinsider.com/cohere-ceo-aidan-gomez-ai-predictions-2024-12