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Neglecting the Basics While Riding the AI Hype Train.

AI Hype Train Station

Some ‘boring’ factors in tech are as crucial as AI.

Isn’t it ironic that ChatGPT prompts you to confirm if you are human?  Anyway, we’re all jumping on the AI Hype train, and no wonder it’s SO useful.  But whilst artificial intelligence (AI) technology, ChatGPT, and LLMs are taking centre stage, it’s crucial to remember the basics.  

AI is about more than rapidly developing solutions. It’s about ensuring the sustainability and reliability of those solutions. As a tech due diligence company, we’ve witnessed the impact of long-term frantic rushing – considerable technical debt and shaky foundations. 

These issues are often ignored until it represents a cyber or reliability issue. For example, we met with a high-performing e-commerce firm with an impressive, adaptable AI-driven front end but left customer data open to the public. And the wrong people found that security hole, causing an issue for the private equity owner.

Private Equity Investment: Why the Basics Matter

From a private equity perspective, fundamental controls are critical. Private equity firms invest substantial amounts into tech companies to achieve significant returns. To make informed investment decisions, they must thoroughly evaluate the long-term sustainability and scalability of the tech company’s products, the soundness of its IP, the efficiency of tech management, and the robustness of financial controls and roadmaps.

For private equity investors, the ‘basics’ aren’t just good practices—they’re risk mitigation strategies. By focusing on these elements, they can better assess the potential of their investments, drive the strategic direction of the companies they invest in, and ultimately maximize returns. 

They aren’t simply investing in the product but in the company’s ability to maintain and grow it effectively and sustainably over time. Therefore, while the allure of advanced AI technology is undeniable, investors must ensure that tech companies stay in sight of these foundational components amidst the hype. 

Keep things secure, patched and operational.

IP Verification and Defence: The Cornerstone of Tech Innovation

Amidst AI hype and excitement, many tech companies sideline intellectual property (IP) management basics. Ensuring the IP is genuine, defensible, and adequately managed is paramount to the company’s long-term success. Tech companies must proactively safeguard their IP rights, often their most valuable assets.

Key measures include:

  • Conducting comprehensive patent searches to validate the uniqueness of their AI solutions.
  • Securing patents to protect their inventions.
  • Developing robust IP management strategies to maintain and enhance the value of their assets.

In a post-merger situation, a firm I worked for bought a Fintech business due to its technology and IP.  While we were integrating the business it transpired, the IP wasn’t something they’d built and was an off-the-shelf package from a vendor.  Not a problem from a capability perspective; the product still worked.  But the firm probably overpaid for the asset.

Scalable and Reliable Solutions: The Path to Sustainable Growth

Many teams produce a significant amount of technical debt in the race to build and deploy AI solutions rapidly. They need to consider scalability and reliability, two fundamental elements that determine the longevity and effectiveness of a product.

As a tech due diligence company, we constantly emphasize the need for scalable architectures and robust testing frameworks to ensure product reliability. Scalability is not an afterthought—it’s a fundamental design principle that must be considered right from the initial stages of product development. Meanwhile, comprehensive testing procedures are essential to ensuring the reliability and performance of AI solutions.

One firm we assessed had ground-breaking AI capability, which was impressive, but to operate, they had to garner all of the higher-end servers within the European region of AWS.  Not practical, expensive and not scalable.

Solid Tech Management: The Heart of a Well-functioning Team

The role of effective tech management in the success of AI projects cannot be overstated. Managers must provide clear direction, communicate effectively, and foster a positive work environment. Tech management that treats people well boosts morale and enhances productivity and innovation.

Unfortunately, the basics of good tech management often get overlooked in a rush to embrace AI. Companies must invest in leadership development and promote a culture of respect, collaboration, and continuous learning. Only then can they hope to build successful AI solutions.

Financial Controls and Robust Roadmaps: The Backbone of Tech Development

AI development isn’t just about creating cutting-edge solutions—it’s also about having a solid financial control system and a robust roadmap. A well-defined roadmap guides the team’s efforts and helps maintain focus amidst the rapidly evolving tech landscape. Meanwhile, sound financial controls ensure efficient resource allocation, helping tech companies navigate the challenging journey from idea to product launch.

Many tech teams we meet lack these fundamental elements, putting their projects and companies at risk. 

The solution? Investing in strategic planning and financial management ensures their AI ambitions are grounded in reality.

Prioritising Fundamentals for Sustainable AI Implementation

In conclusion, while AI offers immense potential, tech companies must remember that successful AI implementation is built on a solid foundation of IP management, product scalability, tech management, financial controls, and robust roadmaps. 

As the AI landscape evolves, let’s remember to address the basics. After all, the future isn’t just about riding the AI hype train—it’s about doing so in a sustainable, reliable, and fundamentally sound way.  AI Due Diligence provides a trailing indicator of issues, and teams must get ahead of these problems before they mount up and compound.

 

Hutton Henry
Hutton Henry
Hutton has worked with Private Equity Portfolio firms and Private Equity funds since 2015. Having previously worked in post-merger integration for large firms such as Ford and HP, Hutton understands the value of finding issues prior to M&A deals. He is currently the founder of Beyond M&A and provides technology due diligence for VC, PE and corporate investors, so they understand their technology risks before entering into a deal.

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