Sebastian Diaz: The AI gamble that can undermine business

Sebastian Diaz, Bench Media

‘While AI’s shortcuts and efficiencies contribute to business success, this reliance comes with significant risks.’

By Sebastian Diaz, head of media innovation, Bench Media

In today’s world of AI-driven advancements, companies face a critical decision: forge ahead with their own internal innovation efforts, or rely on large tech companies to provide off-the-shelf solutions? Companies like OpenAI provide powerful AI tools used by 92% of Fortune 500 companies to automate tasks and enhance decision-making. While AI’s shortcuts and efficiencies contribute to business success, this reliance comes with significant risks.

Lack of flexibility and customisation

When a business partners with a major tech provider, it buys into their ecosystem. While these platforms offer immense power, they are designed for a broad user base, not tailored to individual business needs. The trade-off? Less flexibility and limited control.

In contrast, when a company builds its own AI tools, it retains full control over the innovation process. Solutions can be designed from the ground up to meet the unique requirements of the business. This ensures the technology is fit-for-purpose, rather than adopting a one-size-fits-all approach. Internal development also allows companies the flexibility to pivot. If a particular solution isn’t performing, it can be adjusted, iterated, or even scrapped. External partnerships rarely offer this level of agility, and often, companies discover limitations too late.

Control over data and transparency

Data is the fuel for AI and machine learning. However, when companies use third-party solutions, they often surrender control over how their data is processed, stored, or used. Many tech companies operate with closed systems, limiting insight into how algorithms function and process data. This can lead to compliance risks, inefficiencies, and reliance on systems that don’t fully align with the business’s goals.

By building proprietary AI solutions, companies retain full control over their data, ensuring transparency in how it’s used. This is crucial given the growing landscape of global privacy regulations. Transparency also safeguards businesses against vulnerability to potential risks, such as AI bias or “black box” decision-making, where algorithmic processes are opaque and difficult to audit.

Innovation at your own pace

Tech giants innovate at a rapid pace, which can be both an advantage and a challenge. While they bring impressive advancements to market, businesses that partner with them are often at the mercy of their roadmaps. If a company like Google or Meta deprioritises a tool or feature, businesses relying on it may find themselves without support, or forced to adopt new solutions that don’t align with their strategies.

On the other hand, companies that handle innovation internally can move at their own pace. They can decide when and how to integrate new technologies, ensuring that their solutions align perfectly with business objectives. This internal agility allows businesses to adapt quickly to market changes without waiting for updates or patches from an external provider.

Long-term cost efficiency

Building in-house AI solutions requires an upfront investment in research, development, and testing. While partnering with tech firms may initially seem more cost-effective, companies often face ongoing subscription fees, high licensing costs, and the burden of adapting third-party tools to meet their specific needs. Over time, these costs can accumulate.

Developing proprietary tools eliminates the need for continuous financial outlay to external providers. Companies can fine-tune their solutions, ensuring they remain relevant without incurring additional costs. Owning the technology also removes the risk of being locked into a vendor’s ecosystem, providing more predictability and financial stability in the long run.

Own your own innovation

While there are short-term benefits to partnering with Big Tech, the long-term constraints – lack of flexibility, limited control over data, and ongoing costs – can hinder a company’s growth and innovation potential. Internal innovation offers greater freedom to build customised solutions that fit specific needs, pivot when necessary, and retain control over both data and costs.

In today’s rapidly evolving digital landscape, businesses that take ownership of their innovation will thrive. They will understand their limitations but always look toward creating proprietary solutions that best serve their evolving needs.

Top image: Sebastian Diaz

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