Why Agnostic AI Is the Key To Cost-Efficient, Scalable AI SolutionsWhy Agnostic AI Is the Key To Cost-Efficient, Scalable AI Solutions

Agnostic AI enables businesses to develop AI solutions around their unique requirements, problems and objectives

Kasia Borowska, Managing director at Brainpool AI

January 16, 2025

5 Min Read
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In November 2022, ChatGPT reached one million users in just five days, igniting a global AI frenzy. However, AI’s evolution was not an overnight phenomenon - it came from decades of advancements in machine learning technologies which paved the way for AI’s success. ChatGPT did not invent new capabilities, and it demonstrated how technologies can be packaged to provide true impact, whilst also highlighting the value of user-centric AI models.

ChatGPT is a great example for businesses looking to implement AI. This solution succeeded because it adapted its technology to meet the needs of the masses in a simple and accessible way - highlighting the importance of creating AI solutions molded around user needs and preferences.

In the race to harness the benefits of AI, almost half of businesses leverage off-the-shelf AI solutions. These are pre-built solutions that businesses can implement quickly without needing to develop their own technology. This is the go-to choice for businesses thanks to their quick deployment and lower upfront costs.

However, these solutions are not as effective as they appear. Businesses that implement them will not benefit from a solution that is molded around their unique business needs. Instead, businesses should leverage agnostic AI to unlock all of the benefits this technology has to offer.

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Flexibility First - Using Agnostic AI To Achieve Your Desired Outcomes

The AI hype has led many businesses to fall victim to “AI FOMO” and rush into adoption without a clear strategy. AI FOMO causes businesses to make impulsive, short-term decisions that lack strategic foresight on how best to leverage AI to achieve their desired outcomes. With 80% of AI projects reportedly failing, we must ask ourselves where businesses are going wrong. The answer - many businesses have rushed into AI implementation and leveraged off-the-shelf solutions with the expectation that it will solve all of their unique business problems.

Off-the-shelf AI solutions are designed for broad applicability and to serve the widest audience possible. These solutions have limited flexibility and they will be unable to adapt to the specific needs of a business. Off-the-shelf AI may also offer functionalities that businesses do not need in their efforts to make their solutions relevant to as wide of an audience as possible. This means businesses will be simultaneously paying for solutions they do not need whilst missing out on the functionalities that would address their unique pain points.

Related:AI Myth Busters: What SMBs Really Need To Know

These solutions are also typically trained on very generic datasets which will result in poor performance, especially when off-the-shelf solutions are leveraged to solve complex business problems.

Instead, businesses should look to leverage agnostic AI, which is a curated methodology that allows businesses to pick the optimal approach, or LLM,  to achieve their desired outcome. By leveraging agnostic AI, businesses can remain agile and versatile, and they will have the ability to fine-tune different LLMs to solve unique problems in a “plug-and-play” fashion. This means that rather than relying on one single model to address all challenges, businesses will be free to leverage multiple LLMs and unlock the tailored, cost-effective and efficient solutions they need to solve each unique business problem.

Aside from preventing businesses from molding AI around their unique problems by taking a “cookie cutter approach” to AI implementation, off-the-shelf solutions are also extremely expensive. These solutions require businesses to upload all of their data into the infrastructure of their chosen vendor. This is an extremely time-consuming and expensive process, especially when businesses look to scale their AI applications. Any business that wants to scale their AI will be forced to re-upload their data into that infrastructure, which comes with significant additional costs due to LLM providers’ commercial-based token model.

When leveraging off-the-shelf solutions, businesses will also be forced to surrender their own IP. Surrendering IP ownership will create long-term consequences for businesses that they cannot afford. Any business that does not own its own IP will experience significant barriers when looking to remain competitive in today’s AI-driven business landscape. With the rapid rate of AI development, businesses must realize that long-term success from AI is far from a box-ticking exercise and it requires constant development. Businesses must remember it is your data, your context, and therefore it should be your IP. Businesses that surrender their IP will be left with ineffective AI models and will struggle to remain competitive

Finally, by leveraging off-the-shelf solutions, businesses will be sacrificing compliance for convenience - leaving them unprepared to meet the needs of evolving AI regulation. These solutions lack the flexibility required to be tailored to meet specific regulatory requirements, meaning that businesses will struggle to remain compliant.

Ensuring Long-Term Success With Agnostic AI

To succeed in today’s competitive business environment, organizations must resist the temptation to rush into AI adoption by leveraging restrictive off-the-shelf solutions. By giving into AI FOMO, businesses will be at risk of paying through the roof for ineffective AI solutions which fail to respond to their organization’s problems. Instead, businesses should take a deliberate and proactive approach - grounded in agnostic AI - to unlock sustained success.

With agnostic AI, businesses will be able to develop AI solutions around their unique business requirements, problems and objectives. Most importantly, they will be implementing solutions that can grow alongside their business, whilst also allowing them to respond to technological and regulatory changes at a lower cost and with increased efficiency.

Businesses must stop viewing AI as a race when it is a long-term journey. The key to success for businesses lies in thoughtful planning and an agnostic approach to ensure all AI implementations solve the unique problems they set out to resolve. 

About the Author

Kasia Borowska

Managing director at Brainpool AI, Brainpool AI

Kasia Borowska is a co-founder and managing director at Brainpool AI. Having degrees in mathematics and cognitive sciences, as well as years of corporate experience working in marketing Kasia realized how little of the academic research is actually applied in real life. Kasia’s hope for the future of AI is a partnership between artificial intelligence and Humans, where AI takes on manual, repetitive and time-consuming tasks to allow people to focus on things that matter.

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