Recently, the largest annual get together of the mobile industry, Mobile World Congress (MWC) took place in Barcelona. In my opinion, the biggest themes at MWC in 2017 that are relevant for enterprise customers were the internet of things (IoT), artificial intelligence (AI), platforms, collaboration, and connectivity. These themes underline how mobility is becoming part of the broader digital transformation initiative. I discuss this shift in this separate blog and report. MWC provided several valuable insights for business and technology leaders to align their mobile to their digital strategies:
-> Not everything that claims to be AI is true AI. Many vendors that claimed during MWC to be AI-proficient are in fact able to deliver true machine-learning solutions to generate transformative customer and operational insights. Most solutions that were branded as AI at MWC rely on preprogrammed responses and statistics rather than machine learning.
IBM hosted an artificial intelligent (AI) event at its Munich Watson IoT HQ, where it underlined its claim as a leading global AI and internet-of-things (IoT) platform providers in the enterprise context. AI and the IoT are both very important topics for enterprise users. However, there remains some uncertainty among enterprises regarding the exact benefits that both AI and IoT can generate and how businesses should prepare for the deployment of AI and IoT in their organizations.
One year into the launch of its Munich-based Watson IoT headquarters, IBM invited about one thousand customers to share an update of its AI and IoT activities to date. The IBM “Genius of Things” Summit presented interesting insights for both AI and IoT deployments. It underlined that IBM is clearly one of the leading global AI and IoT platform providers in the enterprise context. Some of the most important insights for me were that:
AI solutions require a partner ecosystem. IBM is well aware of the fact that it cannot provide IoT services on its own. For this reason, IBM is tapping into its existing partner ecosystem. Those partners are not only other vendors. IBM’s ecosystem partnership approach embraces also customers such as Schäffler, Airbus, Vaillant, or Tesco. The event demonstrated how far IBM has matured in living and breathing customer partnerships in the IoT solutions space. For instance, IBM’s cooperation with Visa regarding secure payment experiences for any device connected to the IoT is an example of a new quality of ecosystem partnership.
It's that time of year again! From next Monday (February 27) through March 2, 2017, Mobile World Congress (MWC) will take place in Barcelona. I attended this event (then 3GSM) for the first time in 2005 and it is fascinating to see how the event has morphed from a B2B telecoms technology trade show to one of the largest business conferences around the globe. This year’s MWC theme is “The Next Element” which may seem broad but I quite like this idea that mobile is elemental and has become part of our daily lives. By analogy with the previous industrial revolution, mobile is like electricity: once you have access to it, it is a disruptive enabler of adjacent technologies powering more powerful innovation. Mobile is barely entering its teenage years.
Consumers now use mobile as a sixth sense. If the human senses serve as effortless faculties through which we access information on the world around us, then mobile has become the sixth sense. It brings digital to consumers in their daily lives. It has truly become the face of digital. That’s the main challenge for marketers: as mobile becomes the primary interface between your brand and your customers, you must leverage mobile to accelerate digital transformation and transform the customer experience you deliver. A lot has to happen behind the scenes for marketers to be able to deliver real-time contextual experiences on mobile. That’s why it makes a lot of sense for marketers to spend time in Hall 8.1 where most marketing, advertising and app vendors will be gathered.
Artificial intelligence (AI) is real, albiet maturing slowly. You experience it when you talk to Alexa, when you see a creepily-targeted online ad, and when Netxflix turns you on to Stranger Things. Oh yea, and that self-driving car over there is AI super-powered! AI is indeed cool, but many are scared about how it ultimatley may impact society. Stephen Hawking, Elon Musk, and even the Woz warned that "...artificial intelligence can potentially be more dangerous than nuclear war." In a nutshell, they are concerned about AI that may evolve to outsmart humans and kill people - a valid concern. But, I have another more terrifying concern that would likely be an insidious precursor to runaway, killer AI.
These days it seems like you can't open a newspaper (ok, web browser) without coming across an article on artificial intelligence. Well publicized breakthroughs like Google AlphaGo's unprecedented victories over human Go champions have heralded the promise of a new golden age for AI. Add to that the personification of personal assistants in Apple's Siri and Amazon's Alexa coupled with Salesforce's “resurrection” of Albert Einstein and the rampant proliferation of AI-related startups - and the AI buzz becomes more of a cacophonous clamor.
To put it mildly, this is confusing for businesses, who are trying to determine what is real and what is mere snake oil. Will AI achieve its transformational promise, or will it join the trash heap of over-hyped technologies?
Forrester believes AI will significantly disrupt the way organizations win, serve, and retain customers... eventually. To do this, it will take massive amounts of data to train artificially intelligent systems to perform their jobs well enough to replace their human counterparts.
Much has been written about how artificial intelligence (AI) will put white-collar workers out of a job eventually. Will robots soon be able to do what programmers do best — i.e., write software programs? Actually, if you are or were a developer, you’ve probably already written or used software programs that can generate other software programs. That’s called code generation; in the past, it was done through “next” generation programming languages (such as a second-, third-, fourth-, or even fifth-generation languages), today are called low code IDEs. But also Java, C and C++ geeks have been turning high level graphical models like UML or BPML into code. But that’s not what I am talking about: I am talking about a robot (or bot) or AI software system that, if given a business requirement in natural language, can write the code to implement it — or even come up with its own idea and write a program for it.
Pure AI is true intelligence that can mimic or exceed the intelligence of human beings. It is still a long way off, if it can even ever be achieved. But what if AI became pure — could perceive, think, act, and even replicate as we do? Look to humanity for the answer. Humanity has been both beautiful and brutal:
The beauty of ingenuity, survival, exploration, art, and kindness.
Artificial Intelligence (AI) is not one big, specific technology. Rather, it is comprised of one or more building block technologies. So, to understand AI, you have to understand each of these nine building block technologies. Now, you could argue that there are more technologies than the ones listed here, but any additional technology can fit under one of these building blocks. This is a follow-on to my post Artificial Intelligence: Fact, Fiction, How Enterprises Can Crush It
Here are the nine pragmatic AI technology building blocks that enterprises can leverage now:
■ Knowledge engineering. Knowledge engineering is a process to understand and then represent human knowledge in data structures, semantic models, and heuristics (rules). AD&D pros can embed this engineered knowledge in applications to solve complex problems that are generally associated with human expertise. For example, large insurers have used knowledge engineering to represent and embed the expertise of claims adjusters to automate the adjudication process. IBM Watson Health uses engineered knowledge in combination with a corpus of information that includes over 290 medical journals, textbooks, and drug databases to help oncologists choose the best treatment for their patients.
Forrester surveyed business and technology professionals and found that 58% of them are researching AI, but only 12% are using AI systems. This gap reflects growing interest in AI, but little actual use at this time. We expect enterprise interest in, and use of, AI to increase as software vendors roll out AI platforms and build AI capabilities into applications. Enterprises that plan to invest in AI expect to improve customer experiences, improve products and services, and disrupt their industry with new business models.
But the burning question is: how can your enterprise use AI today to crush it? To answer this question we first must bring clarity to the nebulous definition of AI.Let’s break it down further:
■ “Artificial” is the opposite of organic. Artificial simply means person-made versus occurring naturally in the universe. Computer scientists, engineers, and developers research, design, and create a combination of software, computers, and machine to manifest AI technology.
■ “Intelligence” is in the eye of the beholder. Philosophers will have job security for a very long time trying to define intelligence precisely. That’s because, intelligence is much tougher to define because we humans routinely assign intelligence to all matter of things including well-trained dachshunds, self-driving cars, and “intelligent” assistants such as Amazon Echo. Intelligence is relative. For AI purists, intelligence is more akin to human abilities. It means the ability to perceive its environment, take actions that satisfy a set of goals, and learn from both successes and failures. Intelligence among humans varies greatly and so too does it vary among AI systems.
Two years ago, Forrester made the claim that mobile was the new face of social. With more than 3 billion users worldwide, messaging apps demonstrated one of the fastest-growing online behaviors and passed social networks. The reach of these apps is huge, which presents a strong relationship promise for marketers.