IBM hosted an artificial intelligent (AI) event at its Munich Watson IoT HQ, where it underlined its claim as a leading global AI and internet-of-things (IoT) platform providers in the enterprise context. AI and the IoT are both very important topics for enterprise users. However, there remains some uncertainty among enterprises regarding the exact benefits that both AI and IoT can generate and how businesses should prepare for the deployment of AI and IoT in their organizations.
One year into the launch of its Munich-based Watson IoT headquarters, IBM invited about one thousand customers to share an update of its AI and IoT activities to date. The IBM “Genius of Things” Summit presented interesting insights for both AI and IoT deployments. It underlined that IBM is clearly one of the leading global AI and IoT platform providers in the enterprise context. Some of the most important insights for me were that:
- AI solutions require a partner ecosystem. IBM is well aware of the fact that it cannot provide IoT services on its own. For this reason, IBM is tapping into its existing partner ecosystem. Those partners are not only other vendors. IBM’s ecosystem partnership approach embraces also customers such as Schäffler, Airbus, Vaillant, or Tesco. The event demonstrated how far IBM has matured in living and breathing customer partnerships in the IoT solutions space. For instance, IBM’s cooperation with Visa regarding secure payment experiences for any device connected to the IoT is an example of a new quality of ecosystem partnership.
- AI-based IoT solutions will transform value chains. This shift was demonstrated very clearly by Local Motors, a car design business that relies on additive manufacturing. Local Motors is breaking up the value chain by involving partners in the design and testing phase. Moreover, these stages are tackled in a parallel fashion and include direct feedback loops, much like a software firm would do. Local Motors has also removed certain phases in the value chain altogether, such as moving the go-to-market activities in-house and online. These changes significantly speed up the innovation and go-to-market activities.
- The network edge will play an important role for supporting AI. Not all intelligence can or should be centralized. Smart connected assets will play an important role in distributing intelligence across IoT solutions. Concepts like multi-access edge computing will play an important role for balancing intelligence workloads between a central data base and edge points. CIOs should not ignore the significance of having a well-defined network infrastructure strategy as part of their AI and IoT activities, because AI depends in many ways on having access to remote compute facilities.
Although the event communicated several very interesting AI and IoT end user examples, several aspects could have received more attention:
- A more detailed update of Watson itself. There was surprisingly little discussion about Watson's recently developed capabilities. Watson was almost treated as a given. It would have been useful to get more information on how Watson is emerging. This matters all the more as vague claims by competitors regarding their AI capabilities are increasing, which could be seen at Mobile World Congress 2017.
- Make the customer benefits of AI more tangible. IoT solutions are possible without AI. IBM should explain in more detail how AI delivers added value to IoT solutions. This added value needs to be more quantifiable to help customers with ROI calculations. Defining KPIs that track specific AI-supported business outcomes would go a long way to help customers develop AI initiatives.
- IoT solutions must push deeper into the operational space for manufacturing. Using AI for testing and rapid prototyping with the help of digital twins is well and good. But manufacturing firms need help to push beyond these activities and deploy AI during the actual manufacturing process. Therefore, aspects like material science and blockchain and their impact on supply chains ought to be discussed in more depth.