AI Assistants: The Next User Interface Paradigm


AI powered virtual assistants are poised to replace the “App” paradigm as the primary user interface for electronic devices and the internet. The capabilities of these products will improve dramatically with developments in deep learning technology that will come in four areas: 1. Recognizing queries – voice, gestures, facial expressions, queries embedded in other apps, etc.; 2. Interpreting queries – natural language decoding, context awareness, etc.; 3. Anticipating needs – pattern analysis, context awareness, etc.; and 4. Executing tasks – marshalling resources, managing requests, selecting optimal responses, etc. Long term success will depend upon the progress each company can make in these areas, as well as execution on non-AI factors – 1. Data resources; 2. Engagement with large user bases; 3. Platform integration; and 4. Ecosystem development. GOOGL, uniquely strong across all AI and non-AI factors, has an extraordinary opportunity to re-establish its primacy as a user gateway, not just for information, but, this time, for services as well. MSFT is weak in the consumer market, but well positioned to push Cortana as a unifying enterprise interface tying together its own applications and those of a 3rd party ecosystem. AAPL’s Siri must overcome AI and data weaknesses to sustain the competitive positioning of the iOS platform, while staving off 3rd party challenges from GOOGL, AMZN and FB to displace it amongst iPhone users. Without anchor device platforms to drive primary usage, AMZN’s Alexa and FB’s M could be somewhat marginalized despite excellent AI and, at least in FB’s case extensive user data and massive engagement. For independent apps without AMZN and FB’s user lock-in, AI assistants could prove to be an existential threat.

AI assistants to get much more powerful. We believe that AI will soon drive a revolution in the way users interact with devices and cloud-based services, obviating the app-based GUI that has been, thus far, the hallmark of the mobile era. AI software will accurately interpret queries – spoken and written commands, even gestures and facial expressions – and intuit unexpressed needs – based on context and data rich user profiles – to answer questions and fulfill service requirements with increasing expediency and effectiveness. These assistants will link directly into apps to find information or execute a task, providing a consistent user interface across as many devices as the assistant can reach.

Deep learning fills 4 key roles. 1. Recognition – accurately identifying user queries as they happen, turning sounds into words, gestures into commands, etc., while filtering out irrelevant noise. 2. Interpretation – Determining the true meaning of inputs that may be imprecise, grammatically irregular, dependent on context, or otherwise ambiguous to determine actionable queries. 3. Inference – Predicting user needs based on context (time, place, proximity to other people, etc.), interests/obligations (schedule, previous requests, social connections, etc.), and information (traffic, weather, product availability, etc.) and recommend or even take, actions. 4. Execution – Performing jobs by finding the best answers to questions and employing the most appropriate tools to complete requested tasks.

Critical non-AI requirements. 1. Data – AI developers need massive data bases to design and train their solutions, while the resulting products will need access to broad personal data to effectively operate. 2. Engagement – Integration with applications that already deliver regular user engagement will accelerate reach and adoption. 3. Platform – Integration with device platforms – smartphones, home appliances, game consoles, PCs, etc. – can put AI assistants in front of app interfaces while pushing availability closer to ubiquity. 4. Ecosystem – The value of the assistant is dependent on the range of services that it can command, both those directly controlled and those provided by 3rd party partners.

GOOGL strikes back. A paradigm shift to a single AI powered user interface reverses a trend toward independent apps which had begun to blunt the strength of GOOGL’s search franchise. GOOGL is uniquely strong across all AI and non-AI ingredients winning the virtual assistant race, with a combination of cutting edge technical excellence, massive data assets, and long reach through its dominant applications and leading Android platform. GOOGL Assistant is likely deliver capabilities that none of its rivals will be able to match, and could drive share gains for Android devices and gain traction on competitive platforms.

MSFT Cortana key to enterprise strategy. MSFT’s much discussed weakness in engagement and platform reach amongst consumers is more than offset by its strength in the enterprise. Cortana becomes an interface paradigm fronting not just for Windows, which may become irrelevant, but also for Office365, Dynamics, LinkedIn, and other applications, which certainly will not. Managing the primary user interface as work moves to the cloud greatly advances MSFT’s strategy to deliver value to enterprise customers through intelligent analysis and management of workflows within the organization and out to customers and business partners.

Siri awaits the attacking hordes. AAPL is vulnerable – it has relatively weak AI development capabilities and has eschewed collecting the sort of usage data that its rivals will use to design, train and implement their competing virtual assistants. It will use tight integration to the on-board functions of its devices, its well-established ecosystem of developers, and its iron-fisted control of the 3rd party technology approved to run on its platform to promote Siri to its loyal users while subtly impairing the effectiveness of alternatives. The risk is that superior AI assistants on rival platforms will take device market share and erode AAPL’s ability to command premium prices.

AMZN and FB banging on the door. AMZN’s Alexa is available to a few million consumers via the company’s Echo and Fire products. FB’s M (in beta testing) requires that Messenger be launched before it can be used, slotting it behind platform-integrated solutions like Google Assistant, Siri or Cortana. While both companies have strong AI development teams with access to extensive data resources, and (particularly in FB’s case) impressive engagement from a huge base of users, it will be a reach for either to emerge as a leading primary interface solution vs. the integrated alternatives with direct access to hardware and default software and deep linking into 3rd party apps.

Bad news for apps. AMZN and FB are powerful enough to resist deep linking, and can maintain their strong, independent engagement on their rival’s platforms despite the paradigm shift to AI assistants, even if their dreams of gaining primacy are unrealistic. However, less frequently used apps with more questionable user loyalty face an existential threat, as enabling deep linking erodes differentiation, while blocking it invites irrelevance.

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