Making AI More Practical Through Partnerships

Many companies struggle to bridge the gap between AI’s hype and operational impact.

In the race to harness AI’s promise, collaboration often holds the key to turning lofty ambitions into tangible results.

AI has captivated boardrooms with its promise to transform efficiency and innovation. From generative AI that can draft content or code to machine learning models that predict consumer behaviour, the potential is huge.

Yet behind the excitement lies a sobering reality. Many companies struggle to bridge the gap between AI’s hype and operational impact. In fact, after years of investment and pilot projects, ¾ of companies are yet to unlock real value from AI initiatives.

A recent study of 1,000 senior executives found that only 26% of firms have developed the capabilities to move beyond proof of concept and receive real value. And yet 74% remain stuck in experimentation. The gap between promise vs practice begs the question: how can you make AI practical for your business?

The answer, increasingly, is through partnerships. Similar to how no single technology can solve all a company’s problems, no single organisation can master the complex mix of skills and infrastructure that AI demands.

Teaming up with tech vendors, consulting firms or academics can combine strengths that overcome obstacles unthinkable to face alone. But before we look at how strategic partnerships can help unlock the potential of AI, let’s understand some of the key hurdles first.

What’s Holding Back AI Implementation?

Implementing AI at scale is far easier said than done. Some of the challenges businesses face can slow adoption and end up hindering AI.

The first is talent and skills gaps. With so few AI experts in the world, how can every business compete with companies who have in-house data scientists and machine learning engineers? A full ⅓ of companies admit that a lack of a trained AI workforce is a major barrier to the development of AI.

An AI talent gap has been forming in the last few years. While global AI spending reached upwards of $550 billion, there was an estimated shortfall of 50% of needed roles in 2024. So teams are already on the back foot.

Secondly, integration becomes a challenge when AI doesn’t just plug-and-play into existing systems. Legacy integration is often arduous, with more than 90% of businesses reporting difficulties merging AI into their existing systems. This can be due to a number of factors, but messy or inaccessible data is among the top contenders.

The end result? AI projects remain isolated and stay as proof of concept.

Thirdly, there’s the grey areas of ethical and governance concerns. The important questions about bias, transparency and risk come about because of the decisions of AI or the potential for privacy violations. Almost ¼ of companies cite ethical concerns as a barrier to further AI deployment, with missteps causing backlash in reputational or legal damage.

Focusing on areas that businesses can control is crucial in order to overcome these barriers. These include things like governance, data, risk management, regulatory compliance, and workforce talent (Deloitte).

Finally, there’s the issue with ROI pressures. As it’s expensive and resource intensive to implement, tight budgets will always be an issue. Due to all these concerns, executives are wary of pouring resources into AI without clear, quick returns. This is what puts off 15% of organisations. Financial caution is only compounded by the need for specialised hardware and software, which only the biggest enterprises could afford in the past.

So the hurdles are clearly identified, and all of them create a formidable implementation gap. Roughly 70% of these challenges stem from people and processes rather than the tech itself, but the problems aren’t insurmountable.

This is where strategic partnerships can significantly mitigate these barriers and accelerate AI adoption.

Introducing Partnerships as an AI Practicality Bridge

Just as no company can tackle AI alone, partnerships allow others in the ecosystem to fill capability gaps, share risks and get AI initiatives off the ground much faster.

“Artificial Intelligence … is not merely about cutting-edge algorithms or advanced neural networks—it’s about partnerships.”

ITSoli

The good news is that different types of strategic partnerships can help turn AI from theory into practice.

Partner With Tech Vendors

Your pathway to AI implementation can be much faster if you leverage the platforms and expertise of technology providers. Cloud providers and AI vendors offer ready-made solutions, whether pre-trained models or scalable infrastructure, to save you from reinventing the wheel.

What do you get in return? Reduced cost and time to implement AI, effectively democratising access to advanced capabilities. Just how Netflix teamed up with AWS to deploy a more advanced recommendation service based on personalised suggestions through the use of AI. Borrowing scale and expertise helps make progress in months that vendors on their own could only achieve in years.

Collaborate with Academia

There are challenges bigger than a single company can solve, such as cutting-edge research and best ethical practices. By partnering with academics, businesses can advance the state of AI and develop shared solutions at the same time.

Universities, for example, can grant access to leading research talent, helping to co-develop new AI algorithms or applications, which can then help train the next generation of AI professionals and close the talent pipeline over the long term.

As far as ethics are concerned, collaborating with independent research institutes can allow companies to stay ahead of policy and ensure responsible AI guidelines are in place. It’s a combination of academic rigour and industry data. You also gain access to diverse expertise.

Take Time With Startups

Because AI is so fast moving, engaging with startups can often be the fastest way to source the most innovative ideas. Specialised usage or tools for niche problems can open up new applications that may never have come across the minds of anyone in industry.

Either partnering or investing in AI startups can inject some entrepreneurial spirit into your company’s AI efforts because they’re great at rapid innovation but just lack the scale, whereas large businesses have the scale but can lack that innovation.

Johnson & Johnson partnered with an AI startup to predict the outcomes of patients after surgery. The result? A partnership that delivered a 30% reduction in post-surgery complications through predictive AI analytics.

It’s worth pointing out here that partnerships with startups lets more established firms experiment and learn without going all-in from day one. It’s about reducing the costs of infrastructure development and accelerating time-to-value.

“By collaborating with AI innovators, cloud providers and industry experts, organisations are not only accelerating their AI adoption but also ensuring they do so in an ethical, scalable and industry-specific manner.”

IBM

Making AI Actionable

Strategic partnerships can make the spectrum of AI technologies more actionable for companies of all sizes.

• Generative AI – capitalise on the huge promise of LLMs with automated content creation and chatbots with cloud AI providers or startups with pre-trained models. Even powering products and workflows with external platforms can help leverage the power of AI

• Automation and Machine Learning – streamline business processes by integrating automation software vendors or consulting partners. Collaborative frameworks align with the day-to-day running of your business

• Analytics – machine learning can deliver advanced analytics, helping to discover insights in data and support human decision making. Custom models can overcome some of your biggest hurdles

The access to a collaborative environment, complete with knowledge and capability share, is proving to be the secret sauce for AI implementation. Partnerships provide the supporting network that help you navigate the journey faster and with greater confidence.

From a top level, it’s clear that making AI practical is a team effort. Businesses trying to do it alone in-house are quickly realising the massive pitfalls. It’s those who are forging the right partnerships that are leaping ahead.

By combining your company’s industry knowledge and assets with the right technology, talent or research partners, you can drastically improve your odds of AI success. Because, after all, collaboration is how we convert AI’s vast potential into concrete performance improvements and innovation.

However, I would also stress the need for considering a partnership strategy if you’re looking to invest in AI. Identify your gaps before discovering who can help fill them. Partnerships should be aligned with your AI roadmap so you can accelerate and remove as much risk as possible.

I’m always available for a chat about strategic partnerships. If you’re considering embracing the partnership mindset, and want to lead your company into an AI future where value is created together, I’d be interested in hearing from you.