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  • Writer's pictureOliver Nowak

AI: Where to Start in the Real-World

Updated: 2 days ago

With the transformational potential of AI being clearer than ever before, businesses are under enormous pressure to ride the tidal wave rather than being left behind. But embarking on this journey isn't easy, especially with all the hype and noise around it, you don't know what you can and can't believe. For any business, big, small, technology-advanced or not, the starting point has to be understanding your current standing on the AI maturity scale and a clear vision of where you aim to be 6 months, 12 months and 24 months from now. This begins with an honest assessment of your AI capabilities today, and what a realistic path forward looks like for your business.



Assessing Your AI Maturity

So what does an assessment of your current capability look like? This involves scrutinising your existing infrastructure, talent pool, data management practices, and, importantly, the alignment of your AI initiatives with overarching business objectives. The goal here is not merely to identify where you stand but to understand the gap between your current state and your aspirations.


Envisioning Your AI Future

Once you've mapped out your current position, the next step is to envisage your target AI maturity. This is a strategic exercise that should reflect on your business's unique objectives, competitive landscape, and industry benchmarks. It's about setting a north star for your AI journey, one that resonates with your company's vision and market ambitions. AI isn't a one-size-fits-all solution and, if done properly, is going to look drastically different from business to business.


Bridging the Gap: Crafting Your AI Roadmap

The journey from current to target AI maturity isn't a smooth linear line. It requires a meticulously crafted roadmap, tailored to navigate the complexities of digital transformation. This roadmap should outline:

  1. Strategic Priorities: Identify key areas where AI can drive significant impact, prioritising initiatives based on their alignment with business goals.

  2. Capability Development: Assess the skills and infrastructure needed to elevate your AI maturity. This could involve upskilling your workforce, enhancing your data architecture, or adopting new AI technologies.

  3. Incremental Milestones: Set realistic, incremental milestones to track progress. This keeps the momentum going and provides opportunities for recalibration as you learn from each phase of implementation.

  4. Risk Management: Anticipate potential hurdles and integrate risk management strategies to mitigate them. This includes data privacy considerations, ethical AI use, and ensuring AI solutions are scalable and robust.


Embracing the Journey: Continuous Improvement

Even though I mentioned the need to figure out where you want to be in 6, 12 and 24 months' time, it should never be fixed. Advancing your organisation's AI maturity is a continuous process of learning and adaptation. The people problem is the most complex of all to solve. Success with any major technology demands a culture that embraces experimentation, values data-driven insights, and prioritises the development of AI competencies. Remember, the ultimate goal here isn't technological advancement for the sake of it, but ensuring technology becomes a business enabler that creates targeted, sustainable transformation of your business model.


Conclusion: Success isn't a given

I can't stress enough: be realistic. AI isn't a magic wand and integrating it effectively is going to be enormously challenging, that's what makes it such a big differentiator. But the opportunity is significant with the potential to deliver unprecedented operational efficiencies and customer experiences. That starts with being honest about your current competencies and what aspects of the technology can be integrated and adopted effectively. It's all about generating momentum and proving that the path you're on is the right one for the business overall.

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