For all the engineering successes of robots in the past few years, it’s unclear how the various sub-fields will make money. Past business models appear to be of limited use, so after a recap of the current conundrum, I will speculate on some options.
First, the successes. The Boston Dynamics military robots can run
incredibly fast, traverse uneven terrain, and maintain their balance in
many circumstances. Last fall Amazon renamed its acquired company Kiva
as Amazon Robotics, is hiring aggressively, and
serves reference customers in the supply chains of such firms as The
Gap, Walgreens, and Crate & Barrel. Self-driving cars are becoming
real, and improving, far faster than anyone could have predicted: Tesla
made the Autopilot feature (an enhanced cruise control,
essentially) a software download in 2015; no hardware retrofits were
needed. Drones comprise an essential, if controversial, facet of U.S.
Those engineering successes, however, have not yet translated to
revenue. Amazon appears to be in investment mode, with LinkedIn postings
mentioning a “new robotics platform” that could involve machine vision.
Google/Alphabet is reportedly selling Boston Dynamics,
but the future of the other companies acquired at about the same time is
less clear within the Alphabet/X division of labor. Google’s commitment
to self-driving cars looks to be extensive, but the revenue model —
ads? licensing? OEM? a platform play? — remains
undisclosed, or undiscovered.
Who might buy Boston Dynamics? Its founder, former MIT professor Marc
Raibert, is one of the world’s leading authorities on “legged-ness”
(balance and locomotion). The firm has earned multiple DARPA contract
wins. The company’s robots (especially the towering
humanoid Atlas) can be frightening, the notion of robotic warriors can
scare some people, and the economics of potentially being a defense
contractor, with long procurement and decades-long product support
cycles, don’t work for most start-ups. Amazon has the
deep pockets, and potentially the culture (and Amazon Robotics is
already located outside Boston); it has been frequently mentioned as a
logical landing spot, but the fit of humanoid robots in Amazon’s supply
chain isn’t obvious. Toyota announced a massive
robotics initiative lead by Gil Pratt (formerly at the DARPA Robotics
Challenge, which featured the Atlas as a shared platform) and James
Kuffner (formerly the robotics head at Google). Both men know Boston
Dynamics well. Another bet was placed by Rich Smith
of The Motley Fool: General Dynamics builds land-based weapon systems
(tanks) already, knows the procurement process, and could scale
production of military robots relatively easily.
None of these three companies would surprise me. Some less likely
suitors: the military side of iRobot (which is spinning out of its
now-consumer-oriented parent, also based in Boston); GE (making big bets
on 3D printing, the Internet of Things, and advanced
manufacturing, and with a military clientele); Boeing/Lockheed
Martin/Northrup Grumman. I don’t know that they could write the
necessary check, but the nonprofit SRI might be appropriate for a
pre-revenue technology shop with potential government/defense clients.
Apart from Google, other companies exhibit a lack of certainty.
Daimler’s CEO said last year that his firm did not want to play Foxconn
to anyone’s Apple. Uber then reportedly placed an order for 100,000
S-class Mercedes sedans, some of which could be self-driving.
Terms were not announced, but for those doing the math at home, that’s
$10 billion at current sticker prices, not counting any autonomous
add-ons. (Daimler’s Freightliner unit is leading the way in self-driving
semi trucks, so the autonomous speculation is
not far-fetched.) As far as business models for robotics goes, clearly
one play is selling pickaxes to miners.
What might be some other robotics business models?
Just as GE Capital, GMAC, and other firms carved out niches providing
financing for capital expenditures, there will be a role for companies
that can finance robotics purchases, package the loans for Wall Street,
and service the accounts on all sides of the
transaction. There may be sub-specialties: hospital robots,
amusement-park animatronics, and robotic materials-inspectors (for
airplanes for example) might each require different sorts of business
expertise in the financial realm.
IBM dominated mainframe computing, Unix had its day in the midrange,
Windows enjoyed near-monopoly status in the 1990s, and now Android and
iOS control much of the world smartphone installed base. Will there be a
similar software system for robotics? Possibly,
but the heterogeneity of uses and contexts may mean that no one market
is big enough to spawn a predominant operating system. At the same time,
certain vendors could control crucial IP, much like Qualcomm did and
does on the mobile phone. Maybe one company
cracks machine vision particularly elegantly and becomes the Qualcomm or
Intel Inside of that one subsystem. Traction in mobile robots,
batteries, and privacy audits could each end up branded by a vendor that
supplies the final machine-assembler.
Who could become the trusted third party, much as some websites announce
(TRUSTe et al), that monitors data collection and handling, payments,
identity management, and other functions that will become necessary?
Google had a major trust issue with Glass in
its consumer incarnation; is there some player that could restore
confidence as facial recognition, to give only one example, runs the
risk of becoming abused, then discarded, and eventually rejected in the
Numerous universities, starting with UC-Berkeley and joined recently by
MIT, have added targeted training in various facets of data and
analytics. The same will hold true here. From trade schools to PhD
programs, there will be demand for robot assemblers, installers/systems
integrators, repairers, programmers, designers, and more. “Original”
education as well as retraining will be required.
Unlike computers that sit on a desktop or even reside in a pocket or
purse, computers that move about in the physical world require more
sensors, actuators, robustness/ruggedizing, and batteries. Obviously
some components will come from the usual suspects:
batteries from Panasonic; cameras from Sony, Omnivision, or Toshiba;
design by Huge, Frog, or IDEO; etc. Other specialized components such as
hydraulics, treads/wheels, and casing could present new opportunities
for smaller, more nimble entrants.
As care-bots improve, a visiting nurse service might fold robotic care
into an existing contract: a given individual might receive x hours of
skilled nursing care per month, y hours of semi-skilled nursing, and z
hours of robotic assistance, whether in moving,
play, or monitoring. Similar robotic components could become part of
security services such as Pinkerton or Securitas, safety inspections in
mines or oil drilling, or repairs in places that humans can’t easily
Robots are particularly suited for dull, dangerous, or dirty jobs.
Temp-agency firms such as Kelly hire out people to do some of these, so
it would be a natural extension of the current business to rent out
robots to do nasty things like clean chemical tanks,
sort packages for UPS at peak times, or clean out student apartments
before move-in in August. (There’s already a germ-killing robot used in
hospital bathrooms — why not deploy it in dorms?)
-Hobbyists and gadget-lovers
The personal computer took hold among a subculture that merged political
idealism with what’s now known as “maker” culture. Certainly there are
plenty of people creating 3D printed artifacts, building robots,
experimenting with drones, and even programming
self-driving cars (Google “GeoHot car”). The Jibo social robot wants to
be a core part of the family interactions (albeit of early adopters)
rather than a science-fair project. Absent an obvious home-entertainment
adoption pathway as of now (and robotic toys
like the Aibo could be the breakthrough device), in what room(s) will a
robot reside in a human dwelling? If it’s the workshop, that’s a market,
but nothing like the demand for PCs or smartphones. (The entire U.S.
power tool market is roughly $10 billion.)
That may be the initial play: recall that one of the proposed use cases
for a personal computer in the 1980s was as a recipe repository, but
that hardly turned out to be the PC’s killer app.
-Testing and certification
As robots and self-driving cars move more and more freely among human
populations, the potential for injury will require inspections and
licenses closer to those for private aircraft than for cars or boats.
Given the stakes in liability cases, the certifying
authority will be a major step in market adoption.
The long history of telephones as a less immersive communications
technology suggests that people will readily pay for the ability to “be”
in more than one place at a time. Suitable Technology’s Beam robots
(made famous by Edward Snowdon at TED) could be used
for remote visits to a project team, supplier factory, or art museum.
Paying by the visit/meeting, or the minute, may be the win; selling the
robots may become a secondary consideration if demand pulls said teams,
factories, or museums to offer remote visitation.
That’s a brief list; I trust readers will spot many opportunities that I
missed. More tellingly, companies (some of which are household names)
will soon be reporting results from robotic businesses, and market
forces will put pressure on those business models
from both customer and capital perspectives. In other words, Alphabet’s
sorting-out of its investments portends a much broader testing of the
new regime’s various configurations; picking winners will be slightly
easier once we get a sense of what the contenders