Over 40,000 customers, partners and analysts gathered in Las Vegas last week to attend IBM Think. Think showcased the scale and breadth of the company, with news announced in major areas including cloud computing, Watson, its Apple partnership, blockchain and quantum computing. 

But with this scale comes a challenge for IBM: how to communicate this range of offerings with a clear and simple strategy.  

Let's take a look at the leading announcements and then go deeper into our assessment.

Ginni Rometty Introduces Watson’s Law

CEO Ginni Rometty set the tone for the event with a keynote that introduced "Watson's Law," an IBM catchphrase aimed at capturing the next phase in computing. With the implementation of artificial intelligence (AI), the law suggests, every business has the potential to develop into a "platform company" with methods highly optimized to learn from and reinforce the data that lies at the heart of most companies.

Rometty noted the simultaneous change currently underway in technology and business architectures only happens about every 25 years. IBM is hoping this transition becomes known at 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 telecommunication network.

Demonstrating Success With AI and Watson

AI therefore remained the focus for the majority of the other Think presentations. Since most businesses are currently struggling to gain a commercial edge with AI, the main announcements unsurprisingly focused on making Watson, IBM’s AI 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 in order to build, train and deploy machine learning models. IBM 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 the launch of Data Science Elite Team, a consultancy offering free professional services to assist clients with data science problems and in getting started with AI 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 was tackling the problem. André Coisne, general director of French mobile banking service Orange Bank, told his keynote audience that its Watson-based customer chat assistant 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 chatbots to be ready to handle 500,000 conversations using Watson, delivering a return on investment within one week of launch.

IBM still needs to address the question of to what extent its first-mover advantage in AI with Watson has led to commercial traction. For example, in the company's fourth quarter 2017 results, 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. IBM will need to build on these positives by improving its overall communication on AI across 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 at the moment.

Related Article: Is the IBM Watson Brand Unassailable?

Apple and IBM Partnership Embraces AI

The biggest news from the event came from IBM's three-year-old strategic partnership with Apple. Watson Services for Core ML will combine Apple's on-device machine learning, CoreML, with Watson AI services in the cloud 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 that 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 at Think (a rarity for Apple) to highlight early prototypes from customers including Coca Cola. These demonstrated how AI 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 forward for the alliance and enterprise mobility in general. It gives IBM the opportunity to capture a wider developer audience for its cloud and artificial intelligence solutions in an increasingly competitive landscape and 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.

Learning Opportunities

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).

Related Article: Big, Bigger, Huge: Apple, IBM Create Massive Partnership

Progress in Quantum Computing and Blockchain

IBM also shared a progress report on its key 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. The company stated 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 AI, 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 grants it a solid position to distinguish its cloud services and enabling technologies against key rivals Microsoft, AWS and Google as the cloud wars intensify in the coming years.

'Putting Smart to Work' at IBM

IBM is in an enviable position: it sits at the center 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, Rometty was quick to point out that one of IBM's biggest advantages is having a business model that does not "conflict with our customers."

At the same time though, Think emphasised a key challenge: overcoming hurdles posed by its legacy and size, and communicating a clear and simple strategy. The firm has a huge array of products and an organization 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 Think, the company has a fresh opportunity to reevaluate how it addresses the enterprise space and the perception it wants to create. IBM 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.

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