The evolution of AI integration in organisations: From fragmentation to parallelism
Decidr
SMEs
AI
Broad AI
Generative AI
Business
The way businesses integrate AI needs to change.
For modern companies to truly reap the benefits of AI, they need to shift from fragmented implementations to a holistic approach.
While it's useful for businesses to be using a smattering of generative AI for particular tasks, the speed at which the technology is moving means that this just not innovative enough.
The small productivity wins go out the window when isolated AI, also known as narrow AI, isn’t connected to other parts of the business and therefore needs extra human power to double or triple check that what the AI has spat out is correct and relevant.
Fortunately, we're starting to see a shift in this space, but not nearly fast enough.
The old way: fragmented AI integration
In the early days of AI adoption, many businesses approached AI integration in this fragmented manner. And many still do.
This often means that individual departments — or even single workers — are going rogue and using AI tools for things like content creation at their own whim.
In fact, Microsoft’s 2024 Trend Report reveals that 78% of AI users are still bringing their own tools to work without the knowledge or clearance of their bosses.
This is of course both counterintuitive and has the potential to put a business’ data at risk.
But getting back to sanctioned fragmented AI use – can it be useful? To a certain extent, sure. But none of these use cases consider or harness the broader organisational context.
Take the example of an AI-powered customer service chatbot that has been implemented without integrating into a businesses’ CRM or other customer-facing systems.
This leads to several issues:
- Lack of coherence and communication across departments: AI tools implemented in isolation often fail to communicate effectively with other systems, leading to data silos and fragmented customer experiences.
- Inefficiencies and redundancies: Without a unified approach, different departments might use overlapping AI tools. Rather than solving inefficiencies and wasted resources, it adds to them.
- Difficulty in measuring overall impact: When AI tools are implemented in isolation, it becomes challenging to measure their overall impact on the business. This makes it difficult to justify further, potentially necessary, investment in AI tech.
While using these AI tools undoubtedly offer benefits, they also provide a limited scope for impact due to the fact that they're disconnected from other business functions.
As AI technology has rapidly advanced over the last few years, so too has the understanding of its potential.
Increasingly more businesses are recognising the value of a more unified approach to AI integration.
This is something that we at Decidr call Broad AI: An approach that aligns with the overall business strategy and leverages the technology across all departments.
The new way: Parallel organisations
Comparatively, a more modern strategy for AI implementation for all businesses should be holistic, aligning all departments and functions. This ensures that AI is leveraged to its full potential and that a business is getting the most out of its investment.
The benefits of this approach aren’t just numerous, but imperative to the future of business:
- Improved coordination and collaboration: By integrating AI across all departments, organisations can ensure that their teams are working towards a common goal with the same data.
- Enhanced efficiency and productivity: A unified AI strategy eliminates redundancies and ensures that AI tools are used efficiently. This cuts down on time and resource waste.
- Better data utilisation and insights: With a holistic approach, organisations can leverage data from all departments, leading to stronger insights and more informed decision making.
- Easier scalability and adaptability: A unified AI strategy makes it easier to scale AI initiatives and adapt to changing business needs.
Implementing a parallel organisation approach to AI requires careful planning and execution.
It’s important for businesses to first establish clear goals and vision. Don’t just adopt AI for the sake of it, you need to work out what you want to actually achieve with it and — importantly — ensure that this aligns with your overall business strategy.
You should also think about how you want these AI roles to work together towards your common business goal. How can they compliment each other to actually enhance overall performance?
If you’re not sure where to start with any of this — that’s okay. You’re not alone. That’s why platforms like Decidr provide integrated AI solutions — to offer that seamless integration across all departments in a way that's easy to use and base subsequent data-driven decisions on.
This is important, because while most small businesses don’t have AI or even IT experts in-house – they will be expected to have this tech in the increasingly near future. Customer and market expectations won't wait for you, which is why a unified approach will be key to staying competitive and achieving long term success.