As AI becomes more affordable and attainable, more businesses will perceive failing to invest in it as a competitive disadvantage. However, this is likely to lead to many companies rushing into AI adoption before fully thinking it through.
The key to deploying AI effectively across large operations is ensuring connected ecosystems are in place to deliver value. Otherwise, internal operations will be run in disconnected siloes, causing fractures and increasing the potential for inconsistencies, inefficiencies, missed opportunities and slower decision making.
The IT industry has long recognised the benefits of investing in connected ecosystems. For example, project management tools are often used alongside other pieces of software and integrated into third-party applications so that the progress of tasks can be easily documented, collaboration can be streamlined, and knowledge can be shared. These connected ecosystems often also support powerful automations, where actions in one part of the system can trigger responses elsewhere, keeping everything accessible and synchronised without manual intervention.
As businesses turn their attention towards AI adoption, they must be wary of cutting corners and trying to run before they can walk. By laying the foundations and linking different parts of the project lifecycle into a seamless workflow, they will be able to efficiently track, manage, and optimise their processes, ensuring that AI operations are aligned and transparent across different departments and tools. This will allow them to reap the rewards of AI investment without wasted or duplicated efforts and investment.
The starting point
In the past, companies could afford to wait for large system upgrades, like Enterprise Resource Planning (ERP), to be rolled out over a year or two. However, as the pace of change accelerates, waiting this long has become impractical. For example, by the time the system is implemented, market needs or technologies will have drastically changed.
This is especially true in the age of AI, as we’re experiencing an unprecedented pace of change. If you waited 12 months between ordering an AI solution and implementing it, the needle will have probably moved 12 times already, and the equipment will essentially be outdated. To stay competitive and drive real-time innovation, companies need to have connected systems that can adapt quickly, rather than relying on slow, outdated processes.
Linking the supply chain together
The value of connected ecosystems can also be seen across the wider supply chain and the network of businesses, processes, and systems that contribute to the creation and delivery of a product or service. Think of it like the saying ‘a chain is only as strong as its weakest link.’ If just one business in a supply chain has a connected ecosystem that has enabled it to seamlessly integrate AI, the benefits of this will be limited as the product or service moves through to the next link in the chain. For AI to make a real difference, all companies involved need to be connected and use the same systems. Even if each one has implemented AI in its own way, achieving tangible operational improvements will remain slow and complicated if their ecosystems aren’t linked, as their processes will be incompatible.
Traditionally, companies in a supply chain have operated in silos, with each one using different work management systems and processes at different stages of modernity and advancement. However, as more companies integrate AI, the risk is that some systems will evolve at an accelerated pace compared to those that haven’t adopted AI, creating even greater disparities between adopters and non-adopters across the supply chain. This will lead to stark inefficiencies and ultimately hinder the full potential of the technology. It may also result in non-adopters being shunned from the chain in favour of more technologically advanced competitors.
AI-driven future innovation
Today, AI integration means that operations move faster than ever before. To unlock unprecedented connectivity, value and achieve levels of efficiency previously unattainable through the deployment of AI, businesses must implement effective technology both internally and across the supply chain to create connected ecosystems, where data, workflows, and systems are seamlessly integrated in real time. With this achieved, if a change is made in one area, it can be quickly duplicated across other parts of the chain to achieve the greatest possible benefit.
For this to work well, every business within the ecosystem first needs to get its own house in order. By streamlining their internal systems and processes, they will not only be able to implement AI effectively and avoid siloes and inefficiencies, but they will also be able to apply their new AI capabilities to the latest innovations in areas such as IoT and beyond.
