Creators: Social Robotics Pioneer Cynthia Breazeal Builds Your BFF

Stephanie Overby

Founder and chief scientist Cynthia Breazeal has been a pioneer in the field of social robotics.

Cynthia Breazeal is a pioneer in the field of social robotics—machines capable of recognizing and simulating human emotions. She developed her first robot, called Kismet, in 1999 as part of her doctoral thesis at MIT. Kismet is now on display at the MIT Museum with other early AI artifacts, and Breazeal has co-founded a company, Jibo, to commercialize a much-advanced social robot.

Breazeal envisions a future in which robots are adopted to improve people’s quality of life. “I can see social robots contributing positively in so many different ways,” she says, such as by providing personalized education to children, supporting the elderly in their own homes, and encouraging individuals with their health and wellness goals. “But before we can get there,” she says, “we need to introduce social robots in a natural, humanistic way while also building trust.”

Jibo unveiled what it calls the first “family robot” (also called Jibo)—designed to be an emotionally engaging, fun, and helpful companion in the home—on crowdfunding site Indiegogo in 2014. The project initially raised US$3.6 million from individual backers. Since then, Jibo investors, including venture capital firms Charles River Ventures and Flybridge Capital Partners, have provided another $60 million.

Putting the Emotion in Automation

Jibo leverages key human social cues and features that are reinterpreted for its physical form.

Unlike other AI-powered automatons, social robots are built for engagement. “They prioritize the needs of the people around them and can forge bonds through a highly interactive presence,” explains Breazeal.

The latest Jibo prototype does more than respond to basic commands or questions. Using voice and facial recognition, Jibo can get to know the people with whom it lives, learning their likes and dislikes and becoming more helpful and accurate over time. The robot can recognize different people by voice and face and interact based on what it learns about each person.

And like its human companions, Jibo will seek out interaction. Rather than waiting for input, it will ask questions, make suggestions, or even crack a joke on its own. In the kitchen in the morning, for example, Jibo might greet a parent with, “Good morning, John. I hope you slept well,” while offering the children fun facts based on their interests.

“Today, technology treats us like technology,” says Breazeal. Robot companions must be more than transactional voice boxes; they must become relational and situational—capable of processing and responding with emotions that benefit the circumstances and tenor of different interactions.

Taking a Cue from Disney

While Jibo may behave in a more human-like way than other robots, it looks more like an animated, modern lamp than a humanoid. That’s a deliberate choice. Breazeal is keen to avoid what roboticists term “the uncanny valley,” the point at which robots appear so human that people are unsettled by them. “People enjoy robots that are anthropomorphic and emotionally engaging—but this does not mean the more human-like the better.”

“We have a natural fascination with being able to interact with and relate to the ‘not quite human other.’”

Breazeal and her team look to classical animation—think Disney’s anthropomorphic animals—to create robots that elicit positive human identification but don’t cross over the line to creepiness. “Disney is a great resource for understanding how to create compelling robot characters,” she says.

Thus, Jibo leverages key human social cues and features, like a cocked head, but the team reinterpreted them for Jibo’s physical form. “We have a natural fascination with being able to interact with and relate to the ‘not quite human other,’” Breazeal says. “It captures our imagination and connects to our humanity in a different way.”

It Takes an Ecosystem

Today, the biggest challenge for Breazeal and her team is delivering a product that meets her vision for a “valued, adored, and contributing member of the family” rather than just another piece of home hardware. The company is fine-tuning Jibo’s ability to interact with people in a natural, interpersonal way.

To further expand the robot’s capabilities, the company will soon release the Jibo Software Developer’s Kit so external developers can create applications that take advantage of Jibo’s body movement, screen animations, and voice. “We know that the potential for Jibo is profound,” says Breazeal. “Inviting third-party developers to tap into our platform to develop new content and skills for Jibo will provide our customers with even more value over time.”

A chorus of Jibo robots sings “Happy Birthday.”

Having scrapped earlier launch dates, Jibo now says its first robots will be available in late 2017. “Building the first robot for the home is a complex task, and we’ve made sure to lay the groundwork and build the proper foundation first,” Breazeal says. “This is an uncharted path that takes time and patience.”

Getting Out of the Lab

When Breazeal talks about social robots, she sounds less like an entrepreneur and more like an evangelist: “We have a responsibility not just to launch a product but to advance the social robotics category,” she says. She hopes the technology can “help us to become the people and society we aspire to be.”

After more than two decades at MIT, Breazeal felt compelled to introduce social robots to the mass market because she believes in their potential to transform early education, healthcare, and elder living. “But before we can get to a place where robots can step in and provide advanced support, we need to introduce social robots into our everyday lives,” she says.

Moving from the lab to an early stage company is a big change for Breazeal. “Research is about making scientific advancements and enabling opportunities that are beyond the reach of a commercial enterprise,” says Breazeal. Once you can sell the technology, the problem you’re solving changes. “We’re making social robots more accessible while also building a profitable business.”

Breazeal isn’t running the business day to day—Jibo recruited former Nuance executive Steve Chambers as CEO and Breazeal still works at the MIT Media Lab. But even as Jibo’s chief scientist, where her role is to monitor the development of the robot, assess its performance, and incorporate technological innovation, she must operate within time and resource constraints that are more stringent than in academia.

The challenges of making a saleable product at a profit are worth it, she says, because it will open the door to wide-scale adoption and development of social robotics to solve bigger problems. D!

How To Humanize Marketing In The Age Of Artificial Intelligence

Rushenka Perera

Marketing is not something you do at people. It’s something you do for people. More importantly, it’s something you must do for the individual instead of the masses.

Automation and AI help us market with a more focused view of the individual, and at scale, as everyone is NOT the same. Subsequently, marketing should serve us as individuals instead of cookie-cutter consumers.

To this end, how can we leverage AI to humanize our marketing? Below are five ways to respect individuality using robots.

Make it resonate with our human side

This comes first because it should guide every aspect of our marketing. The best advice for this is: “Don’t tell me about your grass seed, talk to me about my lawn.” In other words, don’t use AI to inundate consumers with statistics about your stellar company. Instead, use it to start an honest conversation about what they value in life. So how do you start that conversation?

Start development with human skills

I’ve written before about the growing personalization of artificial intelligence. As technologies like conversational AI become more important, you must ensure your development team understands human interaction. And yes, marketing needs to talk to IT! You simply cannot survive with IT experts that don’t interact with their audience. To succeed, you must educate your IT and marketing workforce in skills such as active listening, empathy, and imagination.

Learn exactly who you’re talking to

According to media analyst Brian Solis, people use their phones 1,500 times a week. Why wouldn’t they? Mobile media makes us feel connected and empowered. It’s the perfect medium for personalized marketing. With the mountains of data mobile devices create, you have no excuse to not understand your consumers. What are their goals? Where are they going? How is their lawn looking?

Of course, it can be difficult to pull the profile of a person from that pile of data. However, machine learning can draw insights from this information. By integrating machine learning with marketing personalization, you can increase engagement enormously.

Provide personalized services

Marketing is about starting a conversation, so speak to your customer as an individual. To achieve this, invest in conversational AI assistants. As more individuals access services through assistants like Siri, you must secure your brand voice in this space.

Use the data we mentioned above to make your “voice” appealing to your customer. This is much easier when your developers have social conversational skills.

Above all, ensure your consumers can access your offerings without repeating themselves. After that, you must recommend further products and services using the language they’re most likely to respond to.

Engage with communities

As you connect individuals to your organization, they’ll seek out others your brand aligns with. Though you should market to individuals, you must remember that we’re all social creatures. This means you must cater to communities that form around your company.

To grow your communities, use social media monitoring to uncover influencers that can recruit more members. From there, assign AI to engage members and incentivize their participation. Finally, deploy machine learning to manage your growing community.

As you can see, artificial intelligence is an (ironically) effective way to bring humanity back to your marketing.

Visit SAP marketing to learn how SAP technologies can help you engage customers in every interaction across digital marketing channels.

Rushenka Perera

About Rushenka Perera

Rushenka is Head of Marketing at SAP ANZ.

Artificial Intelligence: Everyone Please Remain Calm

Glen Moffatt

I don’t know about you, but I’m starting to tire of the rampant sensationalism surrounding artificial intelligence. Don’t get me wrong – I’m just as excited by the prospects of AI as anyone else, and I don’t begrudge companies or people for their enthusiasm for a shiny new thing. I’m always intrigued by the possibilities of technology in business.

My “AI fatigue,” if that’s a thing, arises from all the doomsday predictions surrounding it. Every one of my social media timelines is overflowing with the fear of the (apparently) impending AI apocalypse. Let us search LinkedIn for five seconds:

AI can manipulate your emotions now! writes one CEO. This guy tells us how to avoid losing our jobs to robots in three easy steps. And how about this for a headline: “The robots are coming.”

Are you scared yet? That’s even before we get out the quotes from the truly big guns like the late Stephen Hawking or Elon Musk. Mr. Musk recently was recently quoted saying, “AI could create an immortal dictator from which we could never escape.”

Let me repeat: are you scared yet?

(Did you click the links above? You probably did. I don’t blame you, and I don’t blame the authors. I clicked those links; in fact, I clicked them again while writing this. Those are some pretty sensational headlines.)

Is there another way to think about this?

But let’s put the apocalypse on hold for a moment and try to view this rapidly emerging technology a little more calmly. I’d like to offer you another perspective on AI, because I think we have good reason to believe that an omnipotent AI is NOT coming to kill or enslave us all.

Why do I think this? Because I think we’ve seen this story before…

Meanwhile, 200 years ago…

I think AI is going through a similar story arc as… electricity. And I think that the AI story is going to – spoiler alert – end the same way.

Yes, electricity. It’s a utility now, and barely an afterthought in your day, but it wasn’t always so. Electricity had its own “1.0” product launch to the public a couple of centuries ago. And I think we can learn from that experience as we launch into AI today.

Consider this: which one am I talking about, AI in 2018, or electricity in 1818?

  • Everyone is talking about it, but only a few people – scientist types – really understand it
  • People are openly divided about whether it’s good or bad
  • People flock to and are informed by popular sensational fiction depicting the technology rising up against its human creators (face it, James Cameron doesn’t do The Terminator unless Mary Shelley does Frankenstein)

Let’s follow the story arc to the ending. Again, which one am I talking about?

  • A few good use-cases emerge, others fall by the wayside
  • The best use-cases are scaled up and standardized
  • The technology becomes a commodified product delivered as a utility
  • People consume the technology without even thinking about it
  • People look back and laugh at the wildly misguided hype from the early days

Electricity solves a million little problems I have every day. So many, in fact, that I don’t even think of them as problems anymore. I don’t have to go out and chop down trees and gather wood to heat my home office – I just turn on my heater. (I could give you lots more examples, but hey, it’s electricity, right? I’m sure you get my point.)

The future of AI looks a lot like the history of electricity

That’s where I think AI is heading. We’re going to find the good use cases, scale them up, standardize and commodify them, and deliver them like a utility through a shared public infrastructure. This has happened before, with electricity, and it is happening again, right now, right before our eyes, with AI as we build it into our cloud-based business software.

AI is going to solve a million little problems that we won’t even recognize as problems anymore, and probably a bunch of other little problems we didn’t even know we had. I won’t have to perform all these tedious tasks at work anymore. After I turn on my office heater, I’ll just turn on the invoicematcher, or the salesforecaster, or the financialperiodcloser, or whatever we wind up calling these little-problem-solving AI agents.

I don’t think AI is coming to kill or enslave us. I think it’s coming to enable us – to free us from our tedious work and allow us to concentrate on new and more interesting things, of which we are no more aware than our predecessors were when they shipped Electricity 1.0 back in 1818.

And so, in conclusion: Cortana, save this document; CoPilot, show me last year’s sales; Alexa, turn on the hall light; and Siri, call Mom.

Read An AI Shares My Office to learn more about why artificial intelligence is poised to be more a coworker and less a replacement.

Glen Moffatt

About Glen Moffatt

Glen Moffatt is a presales enablement director at SAP Canada. He is a technical generalist and communicator, specializing in helping others understand the application of enterprise information technology. He expresses himself in a variety of ways: writing code, conducting software demonstrations, teaching, facilitating design thinking workshops, and presenting to the boardroom.

Hack the CIO

By Thomas Saueressig, Timo Elliott, Sam Yen, and Bennett Voyles

For nerds, the weeks right before finals are a Cinderella moment. Suddenly they’re stars. Pocket protectors are fashionable; people find their jokes a whole lot funnier; Dungeons & Dragons sounds cool.

Many CIOs are enjoying this kind of moment now, as companies everywhere face the business equivalent of a final exam for a vital class they have managed to mostly avoid so far: digital transformation.

But as always, there is a limit to nerdy magic. No matter how helpful CIOs try to be, their classmates still won’t pass if they don’t learn the material. With IT increasingly central to every business—from the customer experience to the offering to the business model itself—we all need to start thinking like CIOs.

Pass the digital transformation exam, and you probably have a bright future ahead. A recent SAP-Oxford Economics study of 3,100 organizations in a variety of industries across 17 countries found that the companies that have taken the lead in digital transformation earn higher profits and revenues and have more competitive differentiation than their peers. They also expect 23% more revenue growth from their digital initiatives over the next two years—an estimate 2.5 to 4 times larger than the average company’s.

But the market is grading on a steep curve: this same SAP-Oxford study found that only 3% have completed some degree of digital transformation across their organization. Other surveys also suggest that most companies won’t be graduating anytime soon: in one recent survey of 450 heads of digital transformation for enterprises in the United States, United Kingdom, France, and Germany by technology company Couchbase, 90% agreed that most digital projects fail to meet expectations and deliver only incremental improvements. Worse: over half (54%) believe that organizations that don’t succeed with their transformation project will fail or be absorbed by a savvier competitor within four years.

Companies that are making the grade understand that unlike earlier technical advances, digital transformation doesn’t just support the business, it’s the future of the business. That’s why 60% of digital leading companies have entrusted the leadership of their transformation to their CIO, and that’s why experts say businesspeople must do more than have a vague understanding of the technology. They must also master a way of thinking and looking at business challenges that is unfamiliar to most people outside the IT department.

In other words, if you don’t think like a CIO yet, now is a very good time to learn.

However, given that you probably don’t have a spare 15 years to learn what your CIO knows, we asked the experts what makes CIO thinking distinctive. Here are the top eight mind hacks.

1. Think in Systems

A lot of businesspeople are used to seeing their organization as a series of loosely joined silos. But in the world of digital business, everything is part of a larger system.

CIOs have known for a long time that smart processes win. Whether they were installing enterprise resource planning systems or working with the business to imagine the customer’s journey, they always had to think in holistic ways that crossed traditional departmental, functional, and operational boundaries.

Unlike other business leaders, CIOs spend their careers looking across systems. Why did our supply chain go down? How can we support this new business initiative beyond a single department or function? Now supported by end-to-end process methodologies such as design thinking, good CIOs have developed a way of looking at the company that can lead to radical simplifications that can reduce cost and improve performance at the same time.

They are also used to thinking beyond temporal boundaries. “This idea that the power of technology doubles every two years means that as you’re planning ahead you can’t think in terms of a linear process, you have to think in terms of huge jumps,” says Jay Ferro, CIO of TransPerfect, a New York–based global translation firm.

No wonder the SAP-Oxford transformation study found that one of the values transformational leaders shared was a tendency to look beyond silos and view the digital transformation as a company-wide initiative.

This will come in handy because in digital transformation, not only do business processes evolve but the company’s entire value proposition changes, says Jeanne Ross, principal research scientist at the Center for Information Systems Research at the Massachusetts Institute of Technology (MIT). “It either already has or it’s going to, because digital technologies make things possible that weren’t possible before,” she explains.

2. Work in Diverse Teams

When it comes to large projects, CIOs have always needed input from a diverse collection of businesspeople to be successful. The best have developed ways to convince and cajole reluctant participants to come to the table. They seek out technology enthusiasts in the business and those who are respected by their peers to help build passion and commitment among the halfhearted.

Digital transformation amps up the urgency for building diverse teams even further. “A small, focused group simply won’t have the same breadth of perspective as a team that includes a salesperson and a service person and a development person, as well as an IT person,” says Ross.

At Lenovo, the global technology giant, many of these cross-functional teams become so used to working together that it’s hard to tell where each member originally belonged: “You can’t tell who is business or IT; you can’t tell who is product, IT, or design,” says the company’s CIO, Arthur Hu.

One interesting corollary of this trend toward broader teamwork is that talent is a priority among digital leaders: they spend more on training their employees and partners than ordinary companies, as well as on hiring the people they need, according to the SAP-Oxford Economics survey. They’re also already being rewarded for their faith in their teams: 71% of leaders say that their successful digital transformation has made it easier for them to attract and retain talent, and 64% say that their employees are now more engaged than they were before the transformation.

3. Become a Consultant

Good CIOs have long needed to be internal consultants to the business. Ever since technology moved out of the glasshouse and onto employees’ desks, CIOs have not only needed a deep understanding of the goals of a given project but also to make sure that the project didn’t stray from those goals, even after the businesspeople who had ordered the project went back to their day jobs. “Businesspeople didn’t really need to get into the details of what IT was really doing,” recalls Ferro. “They just had a set of demands and said, ‘Hey, IT, go do that.’”

Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants.

But that was then. Now software has become so integral to the business that nobody can afford to walk away. Businesspeople must join the ranks of the IT consultants. “If you’re building a house, you don’t just disappear for six months and come back and go, ‘Oh, it looks pretty good,’” says Ferro. “You’re on that work site constantly and all of a sudden you’re looking at something, going, ‘Well, that looked really good on the blueprint, not sure it makes sense in reality. Let’s move that over six feet.’ Or, ‘I don’t know if I like that anymore.’ It’s really not much different in application development or for IT or technical projects, where on paper it looked really good and three weeks in, in that second sprint, you’re going, ‘Oh, now that I look at it, that’s really stupid.’”

4. Learn Horizontal Leadership

CIOs have always needed the ability to educate and influence other leaders that they don’t directly control. For major IT projects to be successful, they need other leaders to contribute budget, time, and resources from multiple areas of the business.

It’s a kind of horizontal leadership that will become critical for businesspeople to acquire in digital transformation. “The leadership role becomes one much more of coaching others across the organization—encouraging people to be creative, making sure everybody knows how to use data well,” Ross says.

In this team-based environment, having all the answers becomes less important. “It used to be that the best business executives and leaders had the best answers. Today that is no longer the case,” observes Gary Cokins, a technology consultant who focuses on analytics-based performance management. “Increasingly, it’s the executives and leaders who ask the best questions. There is too much volatility and uncertainty for them to rely on their intuition or past experiences.”

Many experts expect this trend to continue as the confluence of automation and data keeps chipping away at the organizational pyramid. “Hierarchical, command-and-control leadership will become obsolete,” says Edward Hess, professor of business administration and Batten executive-in-residence at the Darden School of Business at the University of Virginia. “Flatter, distributive leadership via teams will become the dominant structure.”

5. Understand Process Design

When business processes were simpler, IT could analyze the process and improve it without input from the business. But today many processes are triggered on the fly by the customer, making a seamless customer experience more difficult to build without the benefit of a larger, multifunctional team. In a highly digitalized organization like Amazon, which releases thousands of new software programs each year, IT can no longer do it all.

While businesspeople aren’t expected to start coding, their involvement in process design is crucial. One of the techniques that many organizations have adopted to help IT and businesspeople visualize business processes together is design thinking (for more on design thinking techniques, see “A Cult of Creation“).

Customers aren’t the only ones who benefit from better processes. Among the 100 companies the SAP-Oxford Economics researchers have identified as digital leaders, two-thirds say that they are making their employees’ lives easier by eliminating process roadblocks that interfere with their ability to do their jobs. Ninety percent of leaders surveyed expect to see value from these projects in the next two years alone.

6. Learn to Keep Learning

The ability to learn and keep learning has been a part of IT from the start. Since the first mainframes in the 1950s, technologists have understood that they need to keep reinventing themselves and their skills to adapt to the changes around them.

Now that’s starting to become part of other job descriptions too. Many companies are investing in teaching their employees new digital skills. One South American auto products company, for example, has created a custom-education institute that trained 20,000 employees and partner-employees in 2016. In addition to training current staff, many leading digital companies are also hiring new employees and creating new roles, such as a chief robotics officer, to support their digital transformation efforts.

Nicolas van Zeebroeck, professor of information systems and digital business innovation at the Solvay Brussels School of Economics and Management at the Free University of Brussels, says that he expects the ability to learn quickly will remain crucial. “If I had to think of one critical skill,” he explains, “I would have to say it’s the ability to learn and keep learning—the ability to challenge the status quo and question what you take for granted.”

7. Fail Smarter

Traditionally, CIOs tended to be good at thinking through tests that would allow the company to experiment with new technology without risking the entire network.

This is another unfamiliar skill that smart managers are trying to pick up. “There’s a lot of trial and error in the best companies right now,” notes MIT’s Ross. But there’s a catch, she adds. “Most companies aren’t designed for trial and error—they’re trying to avoid an error,” she says.

To learn how to do it better, take your lead from IT, where many people have already learned to work in small, innovative teams that use agile development principles, advises Ross.

For example, business managers must learn how to think in terms of a minimum viable product: build a simple version of what you have in mind, test it, and if it works start building. You don’t build the whole thing at once anymore.… It’s really important to build things incrementally,” Ross says.

Flexibility and the ability to capitalize on accidental discoveries during experimentation are more important than having a concrete project plan, says Ross. At Spotify, the music service, and CarMax, the used-car retailer, change is driven not from the center but from small teams that have developed something new. “The thing you have to get comfortable with is not having the formalized plan that we would have traditionally relied on, because as soon as you insist on that, you limit your ability to keep learning,” Ross warns.

8. Understand the True Cost—and Speed—of Data

Gut instincts have never had much to do with being a CIO; now they should have less to do with being an ordinary manager as well, as data becomes more important.

As part of that calculation, businesspeople must have the ability to analyze the value of the data that they seek. “You’ll need to apply a pinch of knowledge salt to your data,” advises Solvay’s van Zeebroeck. “What really matters is the ability not just to tap into data but to see what is behind the data. Is it a fair representation? Is it impartial?”

Increasingly, businesspeople will need to do their analysis in real time, just as CIOs have always had to manage live systems and processes. Moving toward real-time reports and away from paper-based decisions increases accuracy and effectiveness—and leaves less time for long meetings and PowerPoint presentations (let us all rejoice).

Not Every CIO Is Ready

Of course, not all CIOs are ready for these changes. Just as high school has a lot of false positives—genius nerds who turn out to be merely nearsighted—so there are many CIOs who aren’t good role models for transformation.

Success as a CIO these days requires more than delivering near-perfect uptime, says Lenovo’s Hu. You need to be able to understand the business as well. Some CIOs simply don’t have all the business skills that are needed to succeed in the transformation. Others lack the internal clout: a 2016 KPMG study found that only 34% of CIOs report directly to the CEO.

This lack of a strategic perspective is holding back digital transformation at many organizations. They approach digital transformation as a cool, one-off project: we’re going to put this new mobile app in place and we’re done. But that’s not a systematic approach; it’s an island of innovation that doesn’t join up with the other islands of innovation. In the longer term, this kind of development creates more problems than it fixes.

Such organizations are not building in the capacity for change; they’re trying to get away with just doing it once rather than thinking about how they’re going to use digitalization as a means to constantly experiment and become a better company over the long term.

As a result, in some companies, the most interesting tech developments are happening despite IT, not because of it. “There’s an alarming digital divide within many companies. Marketers are developing nimble software to give customers an engaging, personalized experience, while IT departments remain focused on the legacy infrastructure. The front and back ends aren’t working together, resulting in appealing web sites and apps that don’t quite deliver,” writes George Colony, founder, chairman, and CEO of Forrester Research, in the MIT Sloan Management Review.

Thanks to cloud computing and easier development tools, many departments are developing on their own, without IT’s support. These days, anybody with a credit card can do it.

Traditionally, IT departments looked askance at these kinds of do-it-yourself shadow IT programs, but that’s changing. Ferro, for one, says that it’s better to look at those teams not as rogue groups but as people who are trying to help. “It’s less about ‘Hey, something’s escaped,’ and more about ‘No, we just actually grew our capacity and grew our ability to innovate,’” he explains.

“I don’t like the term ‘shadow IT,’” agrees Lenovo’s Hu. “I think it’s an artifact of a very traditional CIO team. If you think of it as shadow IT, you’re out of step with reality,” he says.

The reality today is that a company needs both a strong IT department and strong digital capacities outside its IT department. If the relationship is good, the CIO and IT become valuable allies in helping businesspeople add digital capabilities without disrupting or duplicating existing IT infrastructure.

If a company already has strong digital capacities, it should be able to move forward quickly, according to Ross. But many companies are still playing catch-up and aren’t even ready to begin transforming, as the SAP-Oxford Economics survey shows.

For enterprises where business and IT are unable to get their collective act together, Ross predicts that the next few years will be rough. “I think these companies ought to panic,” she says. D!

About the Authors

Thomas Saueressig is Chief Information Officer at SAP.

Timo Elliott is an Innovation Evangelist at SAP.

Sam Yen is Chief Design Officer at SAP and Managing Director of SAP Labs.

Bennett Voyles is a Berlin-based business writer.

Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.


Survey: Four Ways Machine Learning Will Disrupt Your Business

Dan Wellers and Dirk Jendroska

We are entering the era of the machine learning enterprise, in which this subset of artificial intelligence (AI) capabilities will revolutionize operating models, shake up staffing methods, upend business models, and potentially alter the nature of competition itself. The adoption of machine learning capabilities will be limited only by an organization’s ability to change – but not every company will be willing or able to make such a radical shift.

Very soon, the difference between the haves and the have-nots of machine learning will become clear. “The disruption over the next three to five years will be massive,” says Cliff Justice, principal in KPMG’s Innovation and Enterprise Solutions team. Companies hanging onto their legacy processes will struggle to compete with machine learning enterprises able to compete with a fraction of the resources and entirely new value propositions.

For those seeking to be on the right side of the disruption, a new survey, conducted by SAP and the Economist Intelligence Unit (EIU), offers a closer look at organizations we’ve identified as the Fast Learners of machine learning: those that are already seeing benefits from their implementations.

Machine learning is unlike traditional programmed software. Machine learning software actually gets better – autonomously and continuously – at executing tasks and business processes. This creates opportunities for deeper insight, non-linear growth, and levels of innovation previously unseen.

Given that, it’s not surprising that machine learning has evolved from hype to have-to-have for the enterprise in seemingly record time. According to the SAP/EIU survey, more than two-thirds of respondents (68%) are already experimenting with it. What’s more, many of these organizations are seeing significantly improved performance across the breadth of their operations as a result, and some are aiming to remake their businesses on the back of these singular, new capabilities.

So, what makes machine learning so disruptive? Based on our analysis of the survey data and our own research, we see four primary reasons:

1. It’s probabilistic, not programmed

Machine learning uses sophisticated algorithms to enable computers to “learn” from large amounts of data and take action based on data analysis rather than being explicitly programmed to do something. Put simply, the machine can learn from experience; coded software does not. “It operates more like a human does in terms of how it formulates its conclusions,” says Justice.

That means that machine learning will provide more than just a one-time improvement in process and productivity; those improvements will continue over time, remaking business processes and potentially creating new business models along the way.

2. It creates exponential efficiency

When companies integrate machine learning into business processes, they not only increase efficiency, they are able to scale up without a corresponding increase in overhead. If you get 5,000 loan applications one month and 20,000 the next month, it’s not a problem, says Sudir Jha, head of product management and strategy for Infosys; the machines can handle it.

3. It frees up capital – financial and human

Because machine learning can be used to automate any repetitive task, it enables companies to redeploy resources to areas that make the organization more competitive, says Justice. It also frees up the employees within an organization to perform higher-value, more rewarding work. That leads to reduced turnover and higher employee satisfaction. And studies show that happier employees lead to higher customer satisfaction and better business results.

4. It creates new opportunities

AI and machine learning can offer richer insight, deeper knowledge, and predictions that would not be possible otherwise. Machine learning can enable not only new processes, but entirely new business models or value propositions for customers – “opportunities that would not be possible with just human intelligence,” says Justice. “AI impacts the business model in a much more disruptive way than cloud or any other disruption we’ve seen in our lifetimes.”

Machine learning systems alone, however, will not transform the enterprise. The singular opportunities enabled by these capabilities will only occur for companies that dedicate themselves to making machine learning part of a larger digital transformation strategy. The results of the SAP/EIU survey explain the makeup of the evolving machine learning enterprise. We’ve identified key traits important to the success of these machine-learning leaders that can serve as a template for others as well as an overview of the outcomes they’re already seeing from their efforts.

Learn more and download the full study here.  


About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

Dirk Jendroska

About Dirk Jendroska

Dr. Dirk Jendroska is Head of Strategy and Operations Machine Learning at SAP. He supports the vision of SAP Leonardo Machine Learning to enable the intelligent enterprise by making enterprise applications intelligent. He leads a team working on machine learning strategy, marketing and communications.