Talent for Artificial Intelligence: a Whole New Ballgame | Market Insights™
The growth of artificial intelligence is impacting talent acquisition and retention for both enterprises and service providers
The growth of artificial intelligence is impacting talent acquisition and retention for both enterprises and service providers
There’s no shortage of books, news articles and comments in social media about how artificial intelligence (A.I.) is shaping our future. Although it’s still blazing a trail, we’re on the brink of A.I. disruption that will change all industries and society at a very deep and fundamental level. I believe it will be one of the next great wealth generators.
My optimism about A.I.’s growing potential arises from many successful use case examples as clear evidence that A.I. is now getting the scale, maturity and the ecosystem in which it can be effective. Although A.I. has been developing for 20 to 30 years, it’s gaining enough elements necessary for a supporting ecosystem.
Major advances in Artificial Intelligence (AI) technology are happening rapidly, and many organizations are excited about the possibilities AI presents. However, some successful companies fail in their innovation efforts to create new value by leveraging disruptive technologies. Others haven’t yet embarked on this innovation journey because they lack use cases. My advice: First define the strategy you’ll use to create value through AI. And Facebook is good role model when it comes to AI strategy.
Your strategy for value creation needs to include how to maximize and expedite the development process. This is the foundational core of Facebook’s strategy. I recently attended a dinner focused on AI at the United Nations. Hosted by UNOPS, attendees included distinguished academics, software companies, government entities and AI leaders in companies successfully using AI.
In the heat of battle in the services industry’s rotation from labor arbitrage to digital, Genpact made a significant move today that signals to everyone it’s playing to win. Genpact announced it signed an agreement to acquire Rage Frameworks, a leader in enterprise Artificial Intelligence (AI) and automation technologies and services. Genpact moved the cheese.
Three aspects of Genpact’s acquisition of Rage are especially significant.
Requirement for Digital Rotation Success
When an arbitrage company such as Genpact thinks about its rotation into digital, it must focus on managing three constituencies: shareholders, internal constituencies and customers.
The Rage Frameworks acquisition helps Genpact manage across all three constituencies, as follows:
Genpact’s bold move is important to watch. How many other arbitrage providers will follow this path of serious investment to accelerate their journey to become digital-first service providers?
In his 1970 book “Future Shock,” author and futurist Alvin Toffler made the argument that the modern world disorients people as it creates so many overwhelming changes that we are unable to handle them. Almost 50 years after the book was published, I was struck by Toffler’s argument during a recent client engagement in which we were helping an enterprise identify virtual agents/chatbots for its customer-facing processes. All of the bots contained a healthy dose of artificial intelligence (AI), and each one was trying to push the envelope.
Is AI starting to overwhelm people to the point that they may get frustrated with developments they cannot fathom or use?
Every day we see and read about new use cases that “wow” us. We are amazed and bedazzled by advances in AI. And some are becoming increasingly commonplace in the consumer arena…just think smart homes.
On the flip side, there have been instances in which consumers have found dealing with these omnipresent home devices scary and frustrating. Humans have already strongly voiced that they don’t need bots to shop. And, feeling the need for peace in their home, they have switched off many of their home assistance devices.
Some may argue that the technology industry, driven by the high intoxication from the ivory towers of Silicon Valley, is getting way ahead of the people who are expected to be the eventual consumers of these technologies. The amount of new AI research and products coming every day out of these factories is mind numbing. A significant number of such products may not have any immediate utility, but they do indeed demonstrate the far-reaching power of such advanced systems.
There is an unending scare around AI, cognitive, and other advanced systems taking away jobs from human beings. In the case of virtual reality, people are entranced by engaging with virtual objects as if they are real. It’s fun, until they realize the negative impacts it can have on their day-to-day lives. And, instead of assuaging such fears, the technology industry continues to create use cases to replace human tasks with robots.
From an enterprise perspective, organizations need to proactively create an AI adoption strategy for their business. Though most now have some vision around using AI technologies, frighteningly few are preparing for the massive change management aspect. Their employees must be comforted around the impact AI can and will have on their lives. Indeed, the significant disruption AI technologies can create within a business context may require a very different approach than other technology adoption we have ever witnessed. Technology vendors need to focus on how AI-enabled systems are assisting or helping human beings. The use cases need to be very precise, clear, and friendly, not overwhelming and complex, which they currently are.
The problem is not AI technology. The problem is the way it is being introduced, and the hyperbole around it that may end up overwhelming a significant portion of the human race, leading to eventual burnout. We are humans, and should create technology for humans. If the very technology we create results in alienating a large percentage of us, we will have failed as a human race. AI systems need to be leveraged for enhancing human lives, not for creating technology marvels that overwhelm people and create the future shock.
Recently, as guest speaker at an event for senior lawyers, I looked at “Artificial Intelligence (AI) and the Shape of Things to come”. I started by asking who was using artificial intelligence. A few hands went up but of course, it was a trick question! I held up my mobile phone and pointed out that everyone using Google or mobile assistants, such as, Siri and Galaxy, is using some form of AI – and it neatly demonstrates that AI has arrived in all our lives in ways we have not even realised.
AI is working its way into all aspect of work, business and leisure. The likes of Amazon Echo and Alexa have brought AI to the home while businesses have started to use AI to handle some of their core functions. Examples include processing invoice payments, insurance claims and customer complaints. In the professions such as legal services, some firms have deployed AI that decides what paragraphs to include in legal contracts. On another front, AI is being used in law enforcement, helping police forces uncover fraud.
AI is here and is touching our lives one way or another, sometimes without us even knowing it. So what is it and what kind of benefits or challenges does it bring? I am not an AI scientist and in this blog, attempt to shine only some light on this vast and fast developing topic.
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
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.
For those of you who don’t know who or what Amelia is, she is IPsoft’s cognitive agent or, in other words, an Artificial Intelligence agent that can converse with people and act as an electronic call center agent. She can do what I would say is at least 30 percent or more of the work currently performed in today’s call centers.
When I met Amelia, she read a Wikipedia article and had a conversation about it with us. She effectively operated similar to an eighth-grader’s ability to synthesize what was in that article and answer questions.
She went on to show how she could converse with us to open bank accounts, help us file insurance claims, or sell us a homeowner’s or car insurance policy. It was natural English and included handling sarcasm, implied questions and answering in a way that was both natural and complete.
As someone who has seen a lot of automation and a lot of neat technologies, I’m truly impressed with Amelia. In terms of usefulness, I put this up there with my experience when I met IBM’s Watson. The difference between the two experiences is that it’s much easier to see how Amelia can immediately take over functions and jobs that I see in everyday life with very little programing and interfaces; whereas, Watson looks to be very powerful (smart) but requires substantial up-front investments to implement. In the use cases where I watched Watson perform, he was a companion to a knowledge worker enabling that worker to perform at a level that, unassisted, the worker would never be able to do alone. Both are very powerful; Watson enables more analytical work, and Amelia eliminates mundane tasks.
Mark me down as a believer that as Amelia is adopted across the industry, this AI technology will transform the customer service industry as we currently know it. I’m a converted fan for both Amelia and Watson and can’t help wondering whether, in some use cases, the two of them should get together and complement each other.
Big data analytics, Service provider convergence, Internet of Things, Productization, Machine learning and automation
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