Author(s): Nicholas McQuire
Over 40,000 customers, partners and analysts gathered in Las Vegas a couple of weeks ago to attend IBM Think 2018. The event showcased the scale and breadth of IBM, with announcements in major areas including cloud computing, Watson, its partnership with Apple, blockchain and quantum computing. But with this scale comes a challenge for IBM: communicating this range of offerings with a clear and simple strategy.
Let's take a look at the top news from the event and then go deeper into our assessment. For a more comprehensive analysis see Enterprise Insight: Event Report: IBM Think 2018.
Ginni Rometty Introduces Watson's Law
IBM CEO Ginni Rometty set the tone for the event with a keynote presentation that introduced "Watson's Law," an IBM phrase aimed at capturing the next phase in computing. She suggested that by implementing artificial intelligence, every business can become a "platform company" with methods highly optimized to learn from and reinforce the data that lies at the heart of most companies.
Ms Rometty noted that the simultaneous change happening in technology and business architectures only happens about every 25 years. IBM is hoping this transition becomes known as Watson's Law, with comparable weight to principles such as Moore's Law, which relates to the doubling of processing power every two years, and Metcalfe's Law, which refers to the impact of the number of users on the value of a telecom network.
Demonstrating Success with Artificial Intelligence and Watson
Artificial intelligence remained the focus for most other presentations. Given that most businesses are struggling to gain a commercial edge through the technology, the main announcements unsurprisingly focused on making Watson, IBM's artificial intelligence platform, more accessible for enterprises.
IBM introduced Watson Studio, a suite of tools for data scientists, developers and domain experts to collaboratively connect to data to build, train and deploy machine learning models. It also unveiled Cloud Private for Data, an integrated data science, data engineering and app-building platform designed to uncover previously unobtainable insights from company data. IBM will supplement these new tools with Data Science Elite Team, a no-fee consultancy that will help clients solve data science problems and in getting started with artificial intelligence projects.
One of the main criticisms of Watson in the past has been its lack of flexibility and the time it takes to train the platform and realize business value. IBM was keen to show how it's tackling the problem. André Coisne, CEO of French mobile banking service Orange Bank, told the audience at his keynote session that its customer chat assistant based on Watson has handled 400,000 conversations since being trained in November 2017. Consulting firm EY claimed it only took 28 days of training for its HR chat bots to be ready to handle 500,000 conversations using the platform, delivering a return on investment within one week of launch.
One question IBM still needs to address is to what extent its first-mover advantage in artificial intelligence with Watson has led to commercial traction. For example, in its results for the fourth quarter of 2017, cognitive revenue grew only 3 percent on an annual basis. IBM said Watson currently serves 16,000 customers, a rise from 8,000 in 2017, with the largest customers paying over $1 million a month. It will need to build on these strengths by improving its communication on artificial intelligence throughout the breadth of its business. This will help improve its position with developers and enterprises in the face of rising competition from Google, Microsoft and Amazon Web Services, all of which are heavily focused on winning mindshare.
Apple and IBM Partnership Embraces Artificial Intelligence
The biggest news came from IBM's three-year-old strategic partnership with Apple. The companies will combine Apple's on-device machine learning, Core ML, with Watson artificial intelligence services in the cloud in a new offering called Watson Services for Core ML. The solution aims to give enterprise app developers access to real-time insights — whether online or offline — inside mobile apps. They also announced the Cloud Developer Console for Apple, a studio that runs on the IBM cloud and lets iOS developers build and test new machine learning features.
Brian Croll, Apple's vice president of product marketing for software, and Mahmoud Naghshineh, IBM's general manager for the Apple partnership, shared the stage (a rarity for Apple) to highlight early prototypes from customers including Coca Cola. These demonstrated how artificial intelligence could supercharge in-field mobile apps in areas such as visual recognition for problem identification, diagnosis and augmented reality applied to machine repair.
The moves are a positive step for the partnership and enterprise mobility in general. They give IBM the opportunity to capture a wider developer audience for its cloud and artificial intelligence solutions in an increasingly competitive landscape. It also provides Apple with a more fertile ground to expand the use of Core ML and ARKit in the enterprise market, especially in important areas such as field service and retail.
Above all, the announcements are vital to the future of enterprise mobility. As a large number of businesses begin projects in artificial intelligence in the coming year, many will look to infuse their first generation of mobile apps with the technology, and they now have a good place to start. In our survey of IT decision-makers conducted in July 2017, for example, respondents estimated that as much as 30 percent of their existing business apps would be enhanced with machine learning capabilities in the next 24 months (see AI Will Change the Workplace Quicker Than We Think).
IBM also shared a progress report on its main future areas of quantum computing and blockchain. In just two years, the company has advanced its quantum computing Q platform from a five qubit machine to a prototype 50 qubit computer working on its cloud. It revealed that more than 80,000 people have used its quantum technology in 3 million experiments ranging from molecular chemistry, natural science and finance.
Blockchain was as prominent as artificial intelligence, cloud and quantum computing at the event. IBM provided several case studies and examples of its applications, with companies such as Maersk and Walmart highlighting their partnerships and quick progression of the technology.
In our view, IBM deserves huge credit for its early recognition of the importance of both technologies. Its first-mover advantage means it's well-placed to distinguish its cloud services and enabling technologies against rivals Microsoft, Amazon Web Services and Google, as the cloud wars intensify in the coming years.
"Putting Smart to Work"
IBM is in an enviable position: it's at the centre of a major transition that shows significant promise. Think did a good job of showcasing the vast range of its assets against its biggest strength of all: expertise in business processes and vertical markets. In a world of constant digital disruption, Ms Rometty was quick to point out that one of IBM's top advantages is having a business model that doesn't "conflict with our customers."
At the same time, Think emphasised that IBM needs to overcome hurdles posed by its legacy and size, and communicate a clear and simple strategy. The company has a huge array of products and an organisation so large that it may not be able to move quickly enough to intercept opportunities. It must think more carefully about simplifying the communication of its strategy in a very noisy marketplace, where attention often gravitates to the likes of Amazon, Google, Microsoft and Alibaba.
With a new chief marketing officer and marketing campaign launched at the event, IBM has a fresh opportunity to re-evaluate how it addresses the enterprise space and the perception it wants to create. It talked about "putting smart to work," but it will need to get a bit smarter on how it communicates and unifies its strategy and messaging throughout its business.
A version of this article first appeared in CMSWire on 29 March 2018.
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