The Reinvention of Digital – IBM Think 2019 Summary
As IBM Think draws to a close for another year, we at DeeperThanBlue, have been reflecting on what we’ve heard there.
We all know that digital technology evolves all the time, continuously branching, growing and changing direction. Even changing the way we think! It’s often difficult to see where these changes originate, as the evolution feels almost organic.
Yet Ginni Rometty, Chair President & CEO of IBM, claims that we’re standing at the beginning of the next chapter of Digital Reinvention. And maybe she’s right!
The previous chapter has been all about data being the basis of competitive advantage, and cloud development has been based on meeting the needs of the customer. Rightly so; without customers, businesses die. Competitive advantage requires quality products (which meet customer needs), exceptional service (which customers expect), value for money (which customers want) and brand awareness (which customers receive).
To date, enterprises have developed customer-facing apps, AI platforms and digital interfaces that engage inexorably with the customer.
But at what cost?
Ideally, the development of customer-facing interfaces goes hand-in-hand with that of in-house digital architecture. But there will be companies out there that have concentrated on the the former, while retaining legacy systems in the background – ‘performing random acts of digital’ in order to stay in the game. Fortunately, all is not lost.
According to Rometty, Chapter 2 of Digital Reinvention will be enterprise driven. The new dawn of digital and AI will encompass scaling-up, hybrid applications and mission-critical apps but to be a success; this chapter will see a step-change in trust.
Rometty also recommended taking a reflective view before looking ahead. What can we take from the previous chapter that will influence what we do going forward? Rometty proposed that there were five key lessons:
- We consider problems from the outside in. How do the customer-facing interfaces affect what we do within our business?
- We consider problems from the inside out. With our own workflow and data driving changes, we need to ensure core internal applications are modernised. This has the added benefit of giving us an internal architecture that will evolve as the business does.
- Ensure that one and two join together. Data and AI must be infused within our workflow, and that this combination and the technology that it is based on gives staff the power to drive changes themselves.
- Leading companies already have an application lifecycle development platform, but to stay ahead, they will need to introduce an AI lifecycle development platform.
- You will never have AI without IA – an Information Architecture. In other words, for AI to be effective, the data you provide should be robust and reliable, and spending 80% of your time developing you IA will allow your AI to take care of itself.
Interesting stuff, I’m sure you’ll agree.
But it wouldn’t be an IBM conference unless they made a few announcements about product launches and these all feed in to Chapter 2 of Digital Reinvention.
Watson Anywhere is the latest release of IBM’s flagship AI interface. It will run, as its name suggests, anywhere: on premise, in the IBM cloud, on an enterprise’s cloud, in public (AWS, Azure, Google Cloud Platform) or private – wherever the user wants it to run. You will all have different requirements, which will vary depending on the applications. Some data must be kept within the business, other data will need to be movable. Some confidential, other data less so. Some data will be required in more than one place at a time, perhaps training one AI service, while running one that is more established. IBM claim that Watson Anywhere will be the most open, scalable AI solution for business in the world.
IBM Business Automation with Watson is a workflow code which integrated moments of intelligence: digital plus AI with the guardrails of business rules built in.
As you would expect, IBM’s research is ongoing, with their R&D teams focusing on three main themes:
- Core AI – the key to making AI scalable is the ability for it to learn from less data.
- Trusted AI – transparency of fairness, explainability and robustness in data handling.
- Scaling AI – using AI to automate AI, where the AI itself selects the most appropriate algorithm to use to process data, rather than the user making the decision.
This is what we learned from just the first twenty minutes of IBM Think 2019. If you want to speak to anyone about this, and understand how AI, Cloud and Application Modernisation can help your business get in touch with the DeeperThanBlue team.