IBM’s Alan Cooke says that today’s business leaders need to be reinventors with a vision to integrate AI with IoT across their business.
All around us in our world today, the convergence of new technologies and intelligent machines is making things smarter and reshaping the future of business. Leading-edge enterprises, both new and old, are leveraging emerging technologies to automate and optimise their business performance.
The top achievers are capturing all forms of data from a variety of interconnected devices and using artificial intelligence-based (AI) applications to plumb that data to reach new levels of operational and financial proficiency. They are reinventing industries, extracting valuable insights from the proliferating data, and creating new opportunities and markets for their business.
These leading-edge companies – the ‘reinventors’ – excel at using customer data and analysing competitors to innovate their products and services. They scrutinise any available data to understand customer needs, and anticipate what customers want. Reinventors are also analysing their competitors’ responses to customer demands.
They also know that internet of things (IoT) data is growing twice as fast as social and computer-generated data. As a result, we can see that they are moving from simply capturing IoT sensor data to leveraging it for competitive advantage.
The foundations of IoT and AI
For many companies, the early applications of IoT are undoubtedly delivering great value. For example, they are reshaping customer experiences by putting consumers into context, and offering new avenues for engagement.
However, reinventors also understand that with the addition of AI, the full potential of IoT can be leveraged for business model reinvention. With AI, reinventors are introducing new products, discovering new opportunities, reducing risk and increasing revenue.
Why? Because traditional methods of analysing structured data aren’t designed to efficiently process the vast amounts of real-time data that stream from IoT devices. This is where AI-based analysis and response becomes critical for extracting optimal value from that data.
To lead in today’s business, you need to have a vision to integrate AI with IoT across your business to enable deeper customer relationships, help find new sources of value through data and accelerate the digital transformation of your business operations.
AI and machine learning
At its heart, the IoT is a data challenge. The traditional approach to programmable computing – in which data is shepherded through a series of pre-determined, if-then-else processes to arrive at outcomes – simply cannot process the degree and kind of data needed to fulfil the true promise of IoT.
With AI and machine learning, systems don’t need to be explicitly programmed. They learn from interactions with users and experiences with the environment. This enables them to keep pace with IoT complexity and havoc.
Meanwhile, machine learning is moving from computer labs and web applications to the physical world, where current levels of digital training data and computing power make it functional and actionable.
This ability to embed learning capabilities within the IoT device itself, plus marry device-centric insights with aggregated intelligence in the cloud, is expected to dramatically improve outcomes.
Putting AI and IoT into action
So, how does this play out within an industry context? Imagine a clothing retailer looking to enhance the in-store customer experience. Gathering data about online shopping habits is easy, but in-store behaviour has traditionally been far more difficult to quantify.
With IoT and AI, a store can combine traditional sources of structured data (supply chain, inventory, RFID tags and point of sale) with new sources of less-quantifiable information (in-store foot traffic, social media and even weather data) to get a more complete understanding of customer behaviour.
As a result, you can correlate the data, identify patterns, and make specific, unbiased recommendations on everything from store layout and merchandising, to supply chain management and product design.
Understanding the journey toward intelligent IoT and automation
For many industries – even those with a mature IoT network – combining IoT with AI can and should be the aspiration. But there are steps that must be taken to fully capitalise on this ambition. We recommend the following:
- Design for a connected, software-driven world. You need to develop and articulate a clear vision of your AI/IoT strategy. Back it up with reinvention roadmaps and execution plans. Communicate this vision to your company stakeholders.
- Create an organisational culture of inclusion. Promote and support collaboration and knowledge-sharing across your employees.
- Equip engineers, developers and operations to deal with unprecedented complexity and technology developments. Enable agile and distributed teams to help deliver the right skills.
- Leverage a broad range of internal and external data across your ecosystem and use that data to design new customer experiences. Evaluate and even include select competitors to innovate your products and services.
- Infuse operations and customer experience with IoT intelligence and automation. AI can enable new classes of IoT products and services that sense, reason and learn.
- Automate and optimise processes to improve quality and operational efficiency with less human and financial risk.
- Develop new revenue sources by transforming products, services and experience with individualised interactions delivered through new services, great design and new features that customers cherish.
And remember, it is a journey.
By Alan Cooke
Alan Cooke is technical leader (CTO) for the Ireland enterprise business unit within IBM. He has 30-plus years’ experience as an IT professional and currently helps hundreds of clients to get the most from their experience of working with IBM and, where appropriate, helping them to improve their business results through the use of IBM’s technology and services.