Tag: AI technology

Microsoft Goes All in on Industry Cloud and AI with $20 Billion Nuance Deal | Blog

Yesterday’s announcement of Microsoft’s acquisition of Nuance Communications signifies the big tech company’s serious intentions in the US healthcare market.

We’ve been writing about industry cloud and verticalization plays of big technology companies (nicknamed BigTech) for a while now. With the planned acquisition of Nuance Communications for US$19.7 billion, Microsoft has made its most definitive step in the healthcare and verticalization journey.

At a base level, what matters to Microsoft is that Nuance focuses on conversational AI. Over the years, it has become quite the phenomenon among physicians and healthcare providers – 77 percent of US hospitals are Nuance clients. Also, it is not just a healthcare standout – Nuance counts 85 percent of Fortune 100 organizations as customers. Among Nuance’s claims to fame in conversational AI is the fact that it powered the speech recognition engine in Apple’s Siri.

Why Did Microsoft Acquire Nuance?

The acquisition is attractive to Microsoft for the following reasons:

  1. Buy versus build: If Microsoft (under Satya Nadella) can trust itself to build a capability swiftly, it will never buy. Last year, when we wrote about Salesforce’s acquisition of Slack, we highlighted how Microsoft pulled out of its intent to acquire Slack in 2016 and launched Teams within a year. Could Microsoft have built and scaled a speech recognition AI offering?
  2. Conversational AI: Microsoft’s big three competitors – Amazon, Apple, and Google – have a significant head start in speech recognition, the only form of AI that has gone mainstream and is likely to be a US$30 billion market by 2025. Clearly, with mature competition, this was not going to be as easy as “Alexa! Cut slack, build Teams” for Nadella
  3. Healthcare: This is another battleground for which Microsoft has been building up an arsenal. As the US continues to expand on its $3 trillion spend on healthcare, Microsoft wants a share of this sizeable market. That is why it makes sense to peel the healthcare onion a bit more

 

What Role Does Microsoft Want to Play in Healthcare?

While other competitors (read Amazon, Salesforce, and Google) were busy launching healthcare-focused offerings in 2020, Microsoft was already helping healthcare providers use Microsoft Teams for virtual physician visits. Also, Microsoft and Nuance are not strangers, having partnered in 2019, to enable ambient listening capabilities for physician to EHR record keeping. Microsoft sees a clear opportunity in the US healthcare industry.

  • Everest Group estimates that technology services spending in US healthcare will grow at a CAGR of 7.5% for the next five years, adding an incremental US$25 billion to an already whopping $56 billion
  • The focus of Microsoft and its competitors is to disrupt the multi-billion ($40 billion by 2025) healthcare data (Electronic Medical Record) industry
  • Erstwhile EMR has been a major reason for physician burnout, which the likes of Nuance aim to solve
  • Cloud-driven offerings such as Canvas Medical and Amazon Comprehend Medical are already making Epic Systems and Cerner sit up and take notice

It is not without reason that Microsoft launched its cloud for healthcare last year and has followed it up by acquiring Nuance.

What Does it Mean for Healthcare Enterprises?

Under Nadella, Microsoft has developed a sophisticated sales model that takes a portfolio approach to clients. This has helped Microsoft build a strong positioning beyond its Office and Windows offerings even in healthcare. Most clients in healthcare are already exposed to its Power Apps portfolio and Intelligent Cloud (including Azure and cloud for healthcare) in some form. It is only a question of time (if the acquisition closes without issues) until Nuance becomes part of its suite of offerings for healthcare.

What Does it Mean for Service Providers?

As a rejoinder to our earlier point about head starts, this is where Microsoft has a lead over competitors. Our recent research with System Integrators (SI) ecosystem indicates that Microsoft is head and shoulders above its nearest competitors when it comes to leveraging the SI partnership channel to bring its offerings to enterprises. This can act as a significant differentiator when it comes to taking Nuance to healthcare customers as SI partners can expect favorable terms of engagement.

Partners' Perceptions

Lastly, this is not just about healthcare

While augmenting healthcare capabilities and clients is the primary trigger for this purchase, we believe Microsoft aims to go beyond healthcare to achieve the following objectives:

  • Take conversational AI to other industries: Clearly, healthcare is not the only industry warming up to conversational AI. Retail, financial services, and many other industries have scaled usage. Hence, it is not without reason that Mark Benjamin (Nuance’s CEO) will report to Scott Guthrie (Executive Vice President of Cloud & AI at Microsoft) and not Gregory Moore (Microsoft’s Corporate Vice President, Microsoft Health), indicating a broader push
  • Make cloud more intelligent: As mentioned above, Microsoft will pursue full-stack opportunities by combining Nuance’s offerings with its Power Apps and Intelligent Cloud suites. As a matter of fact, it plans to report Nuance’s performance as part of its Intelligent Cloud segment

Microsoft: $2 Trillion and Beyond

This announcement comes against the background of BigTech and platform companies making significant moves to industry-specific use cases, which will drive the next wave of client adoption and competitive differentiation. Microsoft’s turnaround and acceleration since Nadella took over as CEO in 2014 are commendable (see the image below). It is on the verge of becoming only the second company to achieve $2 trillion in market capitalization. This move is a bet on its journey beyond the $2 trillion.

Picture2 5

What do you make of its move? Please feel free to reach out to [email protected] and [email protected] to share your opinion.

Stop Trivializing AI: It Is Not Just Automation | Blog

AI is certainly being used to attempt to solve many of the world’s big problems, such as health treatment, societal security, and the water shortage crisis. But Everest Group research suggests that 53 percent of enterprises do not – or are not able to – differentiate between AI and intelligent automation and what they can do to help them compete and grow. This trivialization of AI is both eye opening and frustrating.

While it’s true that automation of back-office services is one strong case for AI adoption, there are many more that can deliver considerable value to enterprises. Examples we’ve researched and written about in the past year include intelligent architecture, front-to-back office transformation, talent strategies, and AI in SDLC.

It’s been said that “audacious goals create progress.”  So, how should enterprises think more creatively and aspirationally in their leverage of artificial intelligence to extract real value? There are three ingredients to success.

Think Beyond Efficiency

Enterprises are experimenting with AI-driven IT infrastructure, applications, and business services to enhance the operational efficiency of their internal operations. We have extensively written about how AI-led automation can drive 10-20 percent more savings over traditional models. But enterprises have far more to gain by experimenting with AI to fundamentally transform the entire landscape, including product design customer experience, employee engagement, and stakeholder management.

Think Beyond CX

Most enterprises are confusing putting bots in their contact center with AI adoption. We discussed in an earlier post that enterprises need to get over  their CX fixation and drive an ecosystem experience with AI at the core. Our research suggests that while 63 percent of enterprises rank CX improvement as one of their top three expectations of artificial intelligence, only 43 percent put newer business model among their top three. We believe there are two factors behind this discouraging lack of aspiration: market hype-driven reality checks (which are largely untrue), and enterprises’ inability to truly grasp the power of AI.

Think Beyond Bots

While seemingly paradoxical, humans must be central to any AI adoption strategy. However, most enterprises believe bot adoption is core to their AI journey. Even within the “botsphere,” they narrow it down to Robotic Process Automation (RPA), which is just one small part of the broader ecosystem. At the same time, our research shows that 65 percent of enterprises believe that AI will not materially impact their employment numbers, and that bodes well for their realization of the importance of human involvement.

And, what do enterprises need to do?

Be Patient

Our research suggests that 84 percent of enterprises believe AI initiatives have a long gestation period, which undoubtedly leads to the business losing interest. However, given the nature of these technologies, enterprises need to become more patient in their ROI expectation from such initiatives. Though agility to drive quick business impact is welcome, a short-sighted approach may straight jacket initiatives to the lowest hanging fruits, where immediate ROI outweighs longer term business transformation.

Have Dedicated AI Teams

Enterprises need AI champions within each working unit, in appropriate size alignment. These champions should be tech savvy people who understand where the AI market is going, and are able to contextualize the impact to their business. This team needs to have evangelization experts in who can talk the language of technology as well as business.

Hold Technology Partners Accountable

Our research suggests that ~80 percent of enterprises believe their service partners lack the capabilities to truly leverage artificial intelligence for transformation. Most of the companies complained about the disconnect between the rapid development of AI technologies and the slowness of their service partners to adopt. Indeed, most of these partners sit on the fence waiting for the technologies to mature and become enterprise-grade. And by then, it is too late to help their clients gain first-mover advantage.

As AI technologies span their wings across different facets of our lives, enterprises will have to become more aspirational and demanding. They need to ask their service partners tough questions around AI initiatives. These questions need to go far beyond leveraging AI for automating mundane human tasks, and should focus on fundamentally transforming the business and even creating newer business models.

Let’s create audacious goals for artificial intelligence in enterprises.

What has been your experience adopting AI beyond mundane automation? Please share with me at [email protected].

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