Category: Automation/RPA/AI

AI Bots: Should Brands be Concerned? Yes, Very | Sherpas in Blue Shirts

Today, users can ask Amazon Echo or Google Home to pay their bills or check their account balances with simple requests following their respective “Alexa” or “OK Google” wake words. Outside the home, various banks are piloting Alexa integration to engage with customers.

Flash forward to tomorrow, when users can launch Amazon’s, Google’s, or another company’s artificial intelligence (AI) bot to book a shared ride car. The users will be impressed when the bot tells them “your car is on the way,” “your car will be there in three minutes,” and “your car has arrived.” They will also hold the AI bot accountable for delivery of the service (even though they ideally shouldn’t.)

But notice I didn’t say launch or hear from Didi Chuxing’s, Lyft’s, Ola’s, or Uber’s app. Indeed, here, the interaction is through the AI bot, and not directly with the brand itself.

While brands spend a fortune on creating exceptional experiences for customers at all touch points, this type of scenario, which will happen, eliminates most, if not all, of those touch points.

So, how should the “brand experience” change?

First, brands should not fight a losing battle. They must understand and accept that AI bots are here to stay, and design their user experiences around them. Brands need to consider AI as their new, or at least a potent, customer engagement model. And, even if brands create their own AI bots to engage with customers, they must align themselves to the market leaders, as users will only have an appetite for a limited number.

Second, there must be a consistent engagement experience, whether the user engages with a bot or directly with the brand. Moreover, frustrated customers will typically blame the brand, not the bot, if things go wrong. This is a concerning reality that brands need to accept and effectively strategize.

Third, this involves significant technology investments. The investments need to drive simplicity in the way services are designed and consumed. The bot world runs on simplicity. It runs on a catalog of services that are fungible, developed on open standards, and demonstrate integration fluidity. Technology that does not cater to this requirement will fall short in the new world. Though some brands may believe that closed-door development creates a better user experience, this won’t be the case in the increasingly complex bot world.

I understand that technology disruption that creates havoc with capabilities and initiatives to drive ideal customer experiences can be overwhelming for brands. And years of investments across channels, touch points, and journeys may appear futile if the bot indeed becomes the customer. After all, machines don’t really care much for “experiences.”

However, brands cannot forget that, irrespective of technology evolution and customer engagement model, they are in the business to create an exceptional customer experience. Brands that understand that their primary, or possibly their only, responsibility is to create customer delight will thrive in this mad digital world.

Legally AI – Disruption in Legal Services and Beyond | Sherpas in Blue Shirts

Artificial intelligence (AI) is working its way into the legal services market at an increasing pace. As robots decide what paragraphs to include in legal contracts and traditional lawyers struggle to maintain the old order, what are the implications for the industry?

There has been litigation support software for years, but intelligent software has now moved on to smarter search and discovery, contracts, analysis and more. A recent, highly publicised example is Berwin Leighton Paisner’s (BLP) contract robot. This AI platform, based on RAVN software, creates legal documents. It reads, interprets and extracts specific information from documents and converts it into a structured output, in a fraction of the time it takes a human, and, perhaps more importantly, with a higher degree of accuracy. In another example, a lawyer from Freshfields in New York has already seen the impact on law firms. He said that in 2006 they had around 60 contract attorneys working on second request matters at any one time. By last year, that figure was just 12 because of predictive coding and electronic review protocols.

We are fast approaching a point where many legal documents will never see a human eye.

Read more in Sarah Burnett’s article at Professional Outsourcing Magazine

Gazing into Everest Group’s Crystal Ball: Enterprise Technology in 2017 | Sherpas in Blue Shirts

It is that time of the year again when we channel our inner psychic about enterprise technology trends. We expect these secular technology trends to play out over 2017 and into early 2018.

  1. The beginning of scary AI democratization
    2016 seemed like the year Artificial Intelligence (AI), and its subset machine learning, turned the corner. A lot of this has been due to the cloud-enabled ease in advancing computing resources, a pre-requisite for AI/machine learning. Self-learning and “intelligent systems” give rise to a multitude of applications. Technology giants such as Amazon, Facebook, Google, IBM, and Microsoft are leading the way through dedicated groups and high-profile hires for advancing the AI mandate. As the technology looks for sizable scale, we are going see the “democratization of AI” help broaden access to its immense potential. For example, Elon Musk’s Open AI alliance released Universe, a software platform for measuring and training an AI’s general intelligence across games, websites, and other applications. Google’s parent Alphabet is putting its entire DeepMind Lab training environment codebase on GitHub. Microsoft is also taking a multi-pronged approach to help make its AI resources available to anyone via the cloud. Although these moves are aimed at catalyzing innovation, only vendors with real skin in the game and an inherent understanding of AI’s potential stand to benefit, limiting the impact system integrators can have via the typical operating model (which is focused on incorporating the latest buzz words in pitch decks and sales collateral). While this democratization will help people accelerate the time-to-value of their AI-enabled initiatives by avoiding the heavy lifting, it will lead to a certain level of commoditization as well. Since every solution will bear the AI tag, enterprises will find it hard to separate the wheat from the chaff. The AI market resembles the cloud wave from some years ago where there was a clot of “cloud-washing” versus “true cloud” implementations. Although the buzz around AI and machine learning is visible from the profile of its varied use cases – whether it is a hedge fund streamlining most of its operational tasks using algorithmic model from its employees’ brains or a law firm hiring an AI lawyer for its bankruptcy practice. Even outgoing U.S. president Barack Obama weighed in, reflecting the importance of AI in shaping our future.
  2. Conversational analytics to focus on engagement
    While conventional analytics – which sounds quite like an oxymoron – will still be viewed through the lens of reporting-descriptive-predictive-prescriptive, conversational analytics and engagement solutions will continue to receive a tremendous fillip. We have analytics engines where one can almost talk or query in human language. At an overall level, this theme represents an amalgamation of product design, natural language processing (NLP), AI, and the platform economy for the right user experience. In the consumer world, Amazon has made it a reality with the Alexa-powered Echo speaker/personal assistant, while Google is trying to replicate that through its assistant-enabled speakers. One particular use case – chat bot – is increasing exponentially, and is now beyond the realm of fancy to tangible use cases across multiple industries. While Facebook Messenger is the most mainstream (consumer-facing) example of these phenomena, there are various interesting experiments across Google (Allo), Microsoft (Tay, Xiaoice), Salesforce (NLUI Server Demo), etc. New conversational analytics offerings will take inspiration from chat bots, and also try to become context-aware for greater value tasks.
  3. SaaS mess becomes messier
    The enterprise applications market is going to witness more bloodshed as legacy and SaaS natives continue to battle it out for supremacy, further stepping on each others’ toes. While Workday leads its surge beyond the HCM domain to financial management, SAP and Oracle will put their considerable resources behind their cloud push. As these players (and others) continue to eat into each others’ pie, there will be an increase blurring of lines between segments and dilution of a unique value proposition. Also, large independent software vendors have confused the market by masking their hosted offerings as SaaS (read: more cloud-washing), which has increased the competitive intensity. Additionally, the SaaS-ification of everything has left the enterprise application landscape looking very messy. CIOs have a considerable governance and management issue when it comes to their app portfolio, upgrades, patches, visibility, usage, etc. You get a feeling that something’s gotta give, and there will be more consolidation among SaaS vendors in the race for market dominance and scale.
  4. Workplaces to move the needle on productivity versus just engagement
    The emergence of Facebook at Work and Slack, (among others), represents the true vision of what is often called the “consumerization of IT.” This refers to the confluence of consumer imperatives such as seamless user experience (UX), BYOD/CYOD convenience, and boundary-less communication within an enterprise IT framework. Digital technologies are reshaping the workplace of the future, while enterprise applications tend to be stuck in a bygone era. Slack/Facebook and their ilk aim to redefine this paradigm. Microsoft has also bought the bait, and launched Teams aka “Slack-killer” in November 2016 (selling it as a part of the Office 365 subscription suite). The focus of these changes has largely been on improving employee engagement, while focus on productivity has been diluted. We expect enterprises to focus more on productivity through differential strategies. Buyers tend to approach these policies in wide variance depending on their business and culture. Think Amazon, which abhors meetings and has a ruthless focus on execution, or Apple, which actively encourages meetings as ideation pods, coming from a culture which is obsessed with making the best products. Bringing machine learning into the mix can help coalesce people, organizational resources, and data. True that workplace collaboration and productivity seems almost unrecognizable.
  5. The automation tsunami will begin to gather speed
    Automation dominated headlines (and earnings calls) in 2016, as enterprises and their service partners alike realized the widespread implications of this technology wave. We believe that the impact on the jobs market is just starting as automation takes roots in mature people-intensive processes/functions. The short-medium kerfuffle will be focused on job losses and pricing pressures, with more pertinent questions around the fundamental nature of employment going forward. 2017 will continue to see similar headwinds, with the bulk of the bloodshed still a couple of years away. Beyond the immediate hullabaloo, the automation narrative is much more profound. While machines can already perform many forms of manual labor, the workforce needs to be reskilled/upskilled to remain relevant as the machines move toward more cognitive tasks. Contrary to popular belief, any wave of industrialization such as automation almost invariably leads to a redistribution in the profile of work, with employees focusing on higher value processes/functions. We are just getting started with the immediate pain that precedes an upward shift in the workforce. Unlike others waves of hyper industrialization, e.g., when cars were invented, there are less systemic problems for technology to solve. Riding this wave will require massive social changes in terms of organizational design, training programs, incentive structures, STEM education, demographic policies, etc.

While most of these themes are already playing out in certain shades, they will gather more wind beneath their sails as we dive into 2017. Although Niels Bohr presciently remarked that “prediction is very difficult, especially if it’s about the future,” we would love to hear what you have to say about enterprise technology in 2017 and beyond.

RPA is Free, so Let’s Discuss Cognitive Now | Sherpas in Blue Shirts

In the midst of increasing RPA adoption in global services, WorkFusion, a technology vendor that focuses on delivering smart automation solutions, has taken a bold move to offer RPA for FREE. While trial or community editions of RPA tools are available for free from RPA technology vendors such as UiPath, WorkFusion’s RPA Express is the first ever scalable and enterprise-grade RPA product to be made available for free and for all.

The adoption of RPA has been increasing rapidly, but it has been skewed toward a few industries and large-sized buyers. WorkFusion’s disruptive move of offering RPA for free will make the business case for it extremely favorable, and will significantly accelerate the adoption of RPA across all industries and buyer sizes. It makes RPA accessible to many, and accelerates trials and proofs of concepts by those that have not yet adopted it.

As organizations realize the benefits of RPA, they are likely to turn to cognitive technologies as the next natural step in their enterprise automation maturity. Availability of free RPA will consequently speed up organizations’ journeys to adoption of cognitive automation. WorkFusion is clearly looking to accelerate those journeys, and transition clients from its free RPA to its integrated RPA and cognitive automation platform, while putting commercial pressure on competitors who do not have a fully-fledged cognitive option to offer.

We believe this to be a very smart move. We think the message here is pretty clear that RPA is becoming table stakes, and the real deal is cognitive automation technologies. Also, it’s worth noting that this seems to be happening much faster than many of us would have predicted, and is a clear example of the “law of accelerated returns” and the exponential evolution of technology we talked about earlier this year in our blog: “Artificial Intelligence: How far or how close?”.

It will be exciting to see how WorkFusion RPA Express compares with the leading RPA technologies that are available in the market on a paid basis. Interestingly, we have conducted an in-depth analysis of WorkFusion’s full RPA capabilities, and overall, they stood up very well to relative assessment against better known RPA technology vendors. The technologies assessed included Automation Anywhere, Blue Prism, Kofax Kapow, Kryon Systems, NICE, Redwood, Softomotive, Thoughtonomy, and UiPath.

To read our complete assessment and analysis, please see our newly published report, “Robotic Process Automation (RPA) – Technology Vendor Landscape with FIT Matrix Assessment – Technologies for Building a Virtual Workforce.”

It’s an AI Haven, My Dear Watson | Sherpas in Blue Shirts

By releasing Haven-on-Demand APIs on Microsoft Azure, HPE is following in the footsteps of IBM. Big Blue made its Watson API’s available on BlueMix a while ago. Furthermore, it recently announced a collaboration with Twilio, a cloud communications platform for developers, as part of which it introduced two new offerings: IBM Watson Message Sentiment and IBM Watson Message Insights, pre-integrated with Twilio’s APIs. This signaled IBM’s willingness to make Watson APIs accessible to a wider community of developers, beyond BlueMix. This is also what HPE is doing by making Haven-on-Demand available on Microsoft Azure.

The two technology giants are not alone in releasing their artificial intelligence APIs. Other technology vendors such as Google have done the same. The IBM and HPE differentiator (for HPE for now and until the details of the CSC deal are finalized) is that they are also IT and business process service providers.  They can leverage their own intelligent technologies to transform client’s services.

The world of services is also changing fast thanks to technology, including automation enabled by both dumb and intelligent software. In particular, in recent years we have seen service providers invest in intelligent technologies to automate their offerings. Apart from IBM and HPE, others include (in alphabetical order) Cognizant Intelligent Automation Platform, Infosys Mana, TCS Ignio and Wipro Holmes. Like it or not, the human intelligence component of IT and business process service provisioning is giving way to machine intelligence, but this is a discussion for another blog.

In the world of services, too, IBM and HPE have a differentiator and that is they are well known technology providers. The other service providers are simply not known for this. They might enter the market for selling intelligent technologies (and in fact some are) but it will be a while before they can grow this line of business. In the meantime IBM and HPE are building a presence in the third-party software apps world. By having their technology embedded in many third-party applications, the tech giants are betting on creating their very own de facto standards for intelligent software to boost future tech and services revenues. Owning an industry standard would make it easier for IBM or HPE to integrate their offerings to automate services in the future and there will be other advantages such as faster adoption and client on-boarding and transitioning.

Their open APIs give IBM and HPE an advantage over both technology and services competitors. Although that’s the current situation, given the rapidly changing technology market, a disruptor could emerge anytime and change this pretty picture. The challenge for IBM and HPE is to increase the number of fully fledged third-party applications that use their API to make it tougher for a disruptor to shake up this burgeoning market.

As far as the technology part of the market goes, of course, IBM and HPE are in competition with the likes of Microsoft and Google who are extremely well versed in the art of getting wide and global adoption of their technologies.

HPE faces another challenge, and that is not to lose focus on this line of business while the spin off and merger of its Enterprise Services with CSC goes through.

Time and again history has shown that wide adoption and availability of applications can boost sales of underlying or enabling technologies, e.g. Microsoft Windows and Android to name but a few. IBM and HPE are looking to do the same in the more complex world of artificial intelligence. This is an area that promises much growth in the coming years, and we will be watching it with interest.

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