Yes, you do need an AI strategy – and here’s how to create one

Forming and implementing an effective AI strategy can feel like a mammoth task, but it’s fast becoming a business essential. Our tech columnist, Bernard Marr, suggests a three-step approach

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Artificial intelligence is perhaps the most transformative business technology that we have ever wielded. The dynamism it brings to every industry, business model and job means that organisations must develop and implement effective AI strategies if they are to thrive in the future. Let‘s take a closer look at why creating such a strategy is not only beneficial but essential.

Why your organisation needs an AI strategy 

There have been phenomenal advances in recent years, such as breakthroughs in machine vision and the emergence of generative AI. These technologies have begun to redefine industries by providing intelligent solutions that can understand, learn and even create content on their own. 

This technology can write computer code, accelerating software development cycles. It can generate images and videos, innovatively producing or modifying content to create personalised and immersive experiences. It can even write novels and poems that reflect deep human emotions. 

It plays a crucial role in data analytics too, helping decision-makers to extract actionable insights from massive data sets. 

The healthcare sector is also reaping the benefits, as generative AI aids medical research by facilitating fast and accurate diagnostics and accelerating the drug discovery process, promising safer and more effective solutions. 

Businesses must stay abreast of these developments if they’re to unlock the unprecedented opportunities that AI promises.

Before you get started 

When companies ask me to help shape their approach to AI, their leadership teams often realise that the implications of the technology could be so wide-ranging that simply overlaying an AI strategy on their existing business strategy is not enough. 

Adapting to the AI revolution means addressing fundamental questions about its impact on your firm’s business model and industry. Leaders must consider the competitiveness and relevance of their business models in an AI-dominated future. They must also explore how AI can bring unprecedented levels of intelligence to products and services, and how it can streamline operations to enable new levels of efficiency. Achieving a deep understanding of, and readiness for, this AI-powered future is key before you move on to identifying use cases.

Step one: find your use cases

Identifying impactful use cases for AI is vital if you’re to maximise its potential in your business. You must engage stakeholders in this process, which involves brainstorming sessions where departments work together to outline strategic use cases promising significant benefits. These could include using intelligent chatbots to improve customer service or implementing predictive maintenance on production lines to reduce unplanned downtime and increase efficiency.

Companies should also identify projects that can deliver value quickly, such as automating routine tasks to free people up to do more valuable work or using AI tools for market analysis to gain rich insights into consumer behaviour. This dual approach not only promises sustainable benefits through long-term strategic projects; it also provides vital early momentum.

I’d recommend defining up to three strategic use cases (where AI will make the biggest difference to your business) and one or two quick wins (projects that promise early tangible benefits without using too many resources). Once you have narrowed down your use cases, you can start considering factors such as ethical, technological, skills and implementation challenges.

Step two: implementation planning

It’s crucial at this point to identify potential roadblocks and address these proactively. That will include setting well-defined goals, schedules and governance structures to guide the implementation process. 

Contingency plans need to be established so that any setbacks can be managed efficiently. The emphasis here should be on flexibility and adaptability. 

Establishing cross-functional teams can encourage diverse approaches to problem-solving. The use of pilots can also help to identify problems early on, allowing for the necessary adjustments to be made before a full roll-out.

Step three: change management

A comprehensive AI strategy must incorporate effective approaches to managing change, with a particular focus on employee engagement. It’s vital to recognise how AI will change people’s jobs and to prepare the organisation for this. 

Transparency and adaptability are the keys to a smooth transition. This entails openly communicating the upcoming changes, while training employees in the skills they will require to navigate the new landscape.

Fostering a culture of continuous learning and resilience can also help the whole organisation to adapt. Leaders should actively engage employees, seeking their feedback and suggestions for creating a workplace that preserves their wellbeing amid all the technological advancements. By doing so, organisations can not only use AI efficiently, but also maintain a motivated and productive workforce.

Where to go from here

With a nuanced understanding of the many aspects of AI, any business can embark on a transformation that will steer it towards greater efficiency and innovation. The roadmap I have laid out here serves to guide firms as they work their way through this complex but rewarding new realm. It also points to a future where the symbiosis of man and machine can unlock unprecedented potential.