10 Business Models That Reimagine The Value Creation Of AI And ML

  • Hannah
  • May 6, 2021
  • Comments Off on 10 Business Models That Reimagine The Value Creation Of AI And ML

Partner — Data, Analytics and AI Consulting at Wipro. Soumen helps enterprises to embrace data and augment cognitive intelligence.

Every day we read about some new AI breakthrough. AI is omnipresent in our everyday lives whether we use mobile devices, wearables or voice assistants or stream our favorite shows. Enterprises control the epicenter of the AI economy, and they drive the innovation through a new trajectory, attracting investors through their impeccably timed innovations promising the new efficiency frontier. A new forecast from IDC Worldwide predicts the AI market will have worldwide revenues surpassing $300 billion in 2024 with a five-year compound annual growth rate (CAGR) of 17.1%.

In this article, I will discuss the 10 business models that monetize AI and reimagine value creation. 

Real-Time ‘CogniSense’

One of the game-changing business models that revolutionize the way we live in the moments of truth and do business is what I like to call “real-time CogniSense.” This model aims to provide real-time services that embed AI into the experience. Imagine walking through an airport with indoor navigation switched on or experiencing a straight-though (zero-touch) grocery store (e.g., Amazon Go). Other innovations include cardless banking, autonomous cars, AI-embedded cityscapes, highways and traffic lights. All these have become a reality through the cognitive edge intelligence platforms. All public cloud providers, enterprise and telecom providers (e.g., Vodafone 5G with edge intelligence) have their edge offerings, while Imagimob has introduced edge AI SaaS.

Immersive AI

Humanizing experiences (HX) are disrupting and driving the democratization and commoditization of AI. These more human experiences rely on immersive AI. By 2030, immersive AI has the potential to co-create innovative products and services navigating through adjacencies and double up the cash flow, opposed to a potential 20% decline in cash flow with nonadopters, according to McKinsey. 

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GAFAM has been an influential force in pioneering and championing deep learning with its core business fabric. NATU and BAT have deeply embedded AI into their most profound route. Google’s Maps and Indoor Navigation, Google Translate and Tesla’s autonomous cars all exemplify immersive AI.

Global AI Marketplace

Global AI marketplace is an innovative business model that provides a common marketplace for AI product vendors, AI studios and sector/service enterprises to offer their niche ML models through a multisided platform and a nonlinear commercial model. Think Google Play, Amazon or the Appstore.

SingularityNet, Akira AI and Bonseyes are multisided marketplace examples. Another innovative B2B platform offered by Amplitude helps tap into AI solutions worldwide. Google’s introduction of a model search platform is a giant step in this direction.

Host, Harbor And Harvest

The host, harbor and harvest business model is ripe for innovators, “first principle” adopters and exponential thinkers. This model centers on developing and delivering models without any expensive compute-intensive work. These zero-capital expenses machine learning models are purpose-built, fast, with scalable computing and a predictable “run cost.” 

Examples of this model include NVIDIA’s GPU, Google’s TPUs, Microsoft, Intel and Qualcomm, which are all frontrunners in this space. Run:AI has introduced computing as a service (CaaS) and built a compute-management platform for orchestrating and accelerating AI. TinyML has made it possible to run increasingly complex deep learning models directly on microcontrollers.

Tools And Platforms

Adopting AI is not just siloed models or algorithms development but involves enterprise-wide collaboration and the model’s operationalization. Tools vendors with comprehensive no-code, low-code platforms (autonomous ML) have introduced the managed service AI in the form of AI as a service(AIaaS) or ML as a service (MLaaS) or often as an embedded AI service. It’s estimated that the global AIaaS market will hit $6 billion to $7 billion by 2023, and the MLaaS Market will reach from $1 billion in 2020 to $8.48 billion by 2026, at a CAGR of 43% over the forecast period (2021-2026).

There are four key business models at play here: anything as a service (XaaS), autonomous AI/ML, cloud-native AI and embedded AI (or pervasive augmented AI). Google Cloud ML, Azure ML, AWS ML, IBM Watson, and Alibaba are significant players in MLaaS services, AI as a Service (AIaaS), and auto ML offerings. The Clarifai image recognition platform, Affectiva’s AI-based emotions and expressions, C3.ai platform have come with their unique XaaS offerings. OpenCV (Open Source Computer Vision Library) API applications infrastructure accelerates the embedded CV use in commercial products. 

‘Glocalize Hiveminds’

The globalization of local talents, or “glocalize” as I like to call it, is an Uber-like talent model that bridges the gaps of AI, ML and data scientists worldwide. This model aims to change the game through a connected economy for both enterprises and professionals.

Kaggle, bitgrit and ClickWorker connect the business and a global network with global and local “hivemind.” This means businesses can connect with data scientists and AI/ML specialists to achieve the best algorithms, complex models or solutions as per business needs.

Embedded AI

Another game-changing business model is pervasive augmented AI. According to Gartner, Inc, it’s expected to generate $2.9 trillion in business value and equal to 6.2 billion hours of worker productivity globally by 2021. Embedded AI amalgamates AI computer visions, NLP, segmentation, clustering, recommendation and prediction algorithms in products and services. It caters to contextual recommendations and introduces new financial and insurance products; micro-learning within fintech, edtech, and regtech; and medical AI products. It embraces AI in the business fabric like Starbucks’ Deep Brew to drive brand personalization engine and optimize labor allocations.

MLaaS and AIaaS are predominantly leveraged as pervasive augmented AI. The “long-tail AI” business model is a form of embedded AI and addresses niche solutions across the industry sectors, whether it’s banking, insurance, healthcare, agriculture or Industry 4.0. For instance, AlphaSense is an AI-powered search engine for investment firms, banks and Fortune 500 companies. In contrast, Tempus, with the assistance of AI, provides precision, personalized and optimized medicine.

These 10 business models aim to realize the full potential of AI and ML. Set your course on the value frontier by reimagining how you operate and putting AI at the heart of everything you do.


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