Ka’Ching! 2016 US Edtech Funding Totals $1 Billion

This is a repost of an article that appeared on EdSurge

Santa proved a little more parsimonious to U.S. edtech companies, which altogether raised an estimated $1.03 billion across 138 venture deals in 2016. Those tallies dipped from 2015, which saw 198 deals that totalled $1.45 billion. (Or, from a different perspective, U.S. edtech companies raised roughly 57 percent of what Snapchat did in its $1.8 billion Series F round.)

In this annual analysis, EdSurge counts all investments in technology companies whose primary purpose is to improve learning outcomes for all learners, regardless of age. This year startups that serve primarily the K-12 market raised $434 million; those targeting the postsecondary and corporate learning sector raised $593 million.

Since 2010, venture funding dollars for U.S. edtech startups have increased every consecutive year. It’s worth noting that even though 2016 marked the end of this trend, the dollar total still surpasses the years before 2015.

The downturn isn’t specific to the education industry but rather reflects a broader slowdown across all technology sectors, says Tory Patterson, managing partner at Owl Ventures. “There’s a broader shift in venture capital where there’s less exuberance companies that haven’t really nailed the business model,” he tells EdSurge.

Dealflow dips has also been felt in the health, real estate, construction and financial technology sectors. Across the globe, venture deals returned to 2014 levels, according to CB Insights. The market uncertainty has led some high-profile companies to hit pause on bigger plans. SoFi, which offers loans and other student services, pushed back plans for its initial public offering this year. Pluralsight, an online learning company that was also expected to IPO, is also on hold.

Venture-backed startups tend to swing between two spectrums, says Amit Patel, a partner at Owl Ventures. On one end are businesses “that grow aggressively but have no revenue associated. The other are those laser focused on business model and revenue. The mood is swinging towards the latter.”

Commitments to “impact” or “mission” aside, all investors—even in education—want to see returns. Often that means converting users into dollars.

“We’ve noticed VCs becoming more selective about their education investments, asking more questions about revenue growth and the leading indicators of product adoption, implementation timelines and ultimately usage,” says Jason Palmer, a general partner at New Markets Venture Partners. Unlike Instagrams and other “5-year consumer internet hits,” more investors, according to Palmer, now realize “it can take 10 or 15 years to build a sustainable education business.”

Breaking Down the Numbers

As in previous years, companies offering tools in the postsecondary and “other” categories out-raised other products. (“Other” includes a mix of products that help business professionals develop skills, are aimed at parents, or are not used in K-12 or higher-ed institutions.)

Expect this trend to continue, says Palmer, as investors come to “a greater recognition that higher education institutions adopt and implement more rapidly than K-12 [schools].” Tuition dollars may be one reason why they have adopted technologies such as student retention and predictive analytics platform. “Colleges and universities are facing financial pressures to keep students who contribute to their revenues. In K-12, you don’t have the same urgency of students as revenue drivers,” he suspects.

This year saw no mega-rounds for startups in the postsecondary sector—unlike 2015, which saw HotChalk, Udacity, Udemy, Coursera and Civitas Learning account for more than $520 million of funding. (Udemy did lead this pack in 2016 with a $60 million round.)

In fact, the biggest funding round of 2016 for a U.S.-based startup went to Age of Learning, which raised $150 million and accounts for 55 percent of the funding total for K-12 curriculum products. The Glendale, Calif.-based company is the developer of ABCmouse, a collection of online learning activities aimed for young children. First developed for the consumer and parent market, the tool is attempting to make headway into schools and classrooms.

Choosier Angels

Angel and seed level funding rounds, which signal investors’ interest in promising but unproven ideas, saw a small decline as well. The 66 deals at this stage are the lowest since 2011, although they totaled $62.5 million—roughly on par with 2014 levels.

Over the past five years, the average value of seed rounds has been increasing, from around $600K in the early years of this decade to roughly $1 million in 2015 and 2016. Discounting edtech accelerators, which typically invest $20K to $150K in startups, the 2016 seed round average actually surpasses $2 million. (We counted 28 such publicly disclosed seed rounds totaling $60.2 million)

Fewer but bigger seed deals are “a sign of maturation in the industry,” says Shauntel Poulson, a general partner at Reach Capital. Unlike previous years, where upstarts and ideas popped up the market, she believes the market is currently in a “stage of consolidation where leaders and proven ideas are emerging.”

Aspiring entrepreneurs ought to pay heed. What this means is that “the bar for seed rounds is getting higher,” Poulson adds. “Before it was about a promising idea and a great team. Now you need to show more traction and even some revenue.” Over the past few years investors have learned that “it’s best to focus on business model sooner rather than later.”

Palmer believes the days where startups could raise money before making some may be over. Expect to get grilled over “revenue growth, product adoption, implementation timelines and ultimately usage,” he says. To round out the questions, “VCs are also starting to ask about product efficacy.”

Looking Ahead

Unsurprisingly, investors held a cheery outlook for 2017, expecting funding totals to hold steady or even increase. More companies will be able to demonstrate sustainable revenue, predicts Owl Ventures’ Tory Patterson, and in turn woo investors’ appetite. “We think a lot of companies will be able to hit the $10 million revenue milestone.”

Emerging technologies such as artificial intelligence, augmented and virtual reality could drive further investments as their applications to help improve learning outcomes become clearer. Also expect to see Chinese investors paying closer attention, says Poulson. “There’s a big after-school market [in China] and an opportunity to leverage a lot of the content that’s being developed in the U.S.”

There’s also word on the street that several education-focused venture firms have re-upped their coffers with new funds to support proven, maturing startups. Stay tuned for more details.

Disclosure: Owl Ventures and Reach Capital are investors in EdSurge

Artificial Intelligence is Reshaping Life On Earth: 101 Examples

I recently read this article on gettingsmart.com and thought it would be great to share the list.

This month I’ve been tracking news headlines to get a sense for how widespread AI applications have become. With a couple news alerts and searches I spotted 101 current applications–no SciFi here, these are tools people are using today. And these aren’t just clever algorithms–they are getting better and smarter the more data they interact with.

Life & Media

  1. Mapping apps and satellite view (Google Earth)
  2. Speech recognition (TechCrunch)
  3. Dating apps (Vancouver Sun)
  4. Language translation (Silicon Valley Business Journal)
  5. Image recognition (Fei-Fei Li on TED)
  6. AI composition and music recommendations (Newsweek)
  7. Make reservations at a restaurant. (Techcrunch)
  8. Filters content and make recommendations (Hubspot podcast)
  9. Write articles (Recode)
  10. Optimize website-building (TechCrunch)
  11. Manages prayer requests (Deseret News)
  12. Track and store the movements of automobiles, trains, planes and mobile phones (IBM)
  13. Track real-time sentiments of billions of people through social media (IBM)
  14. Beat the best humans in chess and Go (CCTV)
  15. Coaching social emotional relationships (Phys)

Safety & security

  1. Security-driven AI systems can easily detect and identify bad behaviors from good behaviors. (Economic Times)
  2. Quickly find security vulnerabilities (Defense One)
  3. Criminal justice system is increasingly using algorithms to predict a defendant’s future criminality (Propublica)
  4. Anomaly detection using machine vision (IBM)
  5. Predictive models for crime (IBM)
  6. Autonomous aerial and undersea warfighting (Nextgov)
  7. Guide cruise missiles (Express)

Industry & Agriculture

  1. Optimize crop yield (Amr Awadallah in Forbes)
  2. LettuceBot reduces chemical use by 90% (Wired)
  3. Driverless tractors (Business Wire)
  4. Manufacturers predict which machines will breakdown (Amr Awadallah in Forbes)
  5. Smart robots for repetitive jobs from apple picking and  sneaker maker, (Techcrunch)
  6. Robots develop and share new skills (MIT)


  1. Driverless cars (Nature) coming to Pittsburgh this fall (Wired)
  2. Driverless trucks (TechCrunch)
  3. Managing drone traffic (Yahoo)
  4. Making bus routes smarter (Shanghai Daily)
  5. Improve the efficiency of public transportation systems (IBM)
  6. Oil exploration efficiency (Oil Price)


  1. Prediction and management of pollutants and carbon footprints. (IBM)
  2. Make data centers, power plants, and energy grids more efficient (Money)

Medicine & Health

  1. Digitized health records and all medical knowledge to improve diagnosis (IBM)
  2. Performing cohort analysis, identifying micro-segments of similar patients, evaluating standard-of-care practices and available treatment options, ranking by relevance, risk and preference, and ultimately recommending the most effective treatments for their patients (IBM)
  3. Power precision medicine (NIH)
  4. Reduction of medical errors (H&HN)
  5. Study the genetics of Autism (SAC)
  6. Analyze genomic sequences to develop therapies (Amr Awadallah in Forbes)
  7. Read x-rays better than a radiologist (nanalyze)
  8. Genomic editing–which may be the most important (and scariest) item on the list (Time)
  9. Use social media to diagnosis depression and mental illness (Tech Times)

Organizational Management

  1. Speeding and improving Identity verification and background checking (PE Hub)
  2. Monitor employee satisfaction and predict staff turnover (HuffPost)
  3. Sorting through stacks of résumés from job seekers. (Propublica)
  4. Replace handcrafted rule-based systems (TechRepublic)
  5. Smart virtual assistants (Slate)
  6. Enterprise tech companies provide deep learning as a service–AI on demand (TweakTown)
  7. Humans and robots will increasingly collaborate on problem solving (Quartz)
  8. Automated floor cleaning (Slate)

Art & Architecture

54. Organic algorithms in architecture (Greg Lynn on TED)

  1. Virtual reality art (Wired)
  2. Synthesized music (Newsweek)

Social services & Infrastructure

  1. Timely and relevant answers to citizens (IBM)
  2. Predict the needs of individuals and population groups, and develop plans for efficient deployment of resources. (IBM)
  3. Prediction of demand, supply, and use of infrastructure (IBM)
  4. Mobile phone network services (RCRwireless)
  5. Analysis of lead contamination in Flint water (Talking Machines)
  6. improve building and city design (Property Report)
  7. Poverty map of Africa to improve services delivery (Yahoo)

Finance and Banking

  1. Fraud detection (Business Insider)
  2. Scan news, spot trends and adjust portfolios (Hubspot podcast)
  3. Determine credit scores and qualify applicants (Propublica)
  4. Find the best insurance coverage at the right cost (IBM)
  5. Deliver personalized service with reduce error rates (Finextra)
  6. Handle 30k banking customer services transaction/month (American Banker)
  7. Answer 100M financial questions involving complex data (Fast Company)
  8. Auto-adjudication of insurance claims (Fast Company)
  9. Tax preparation (CFO)

Marketing & Customer Service

  1. Power chatbot customer service (CB Insights)
  2. Product recommendations (Digital Marketing Blog)
  3. Manage White House comments (Techcrunch)
  4. Chatbot lawyer contests parking tickets (Guardian)
  5. Robot inventory checker (NY Times)
  6. Recognise customer behavior and provide predictive customer service (Brand Equity)
  7. Predict eBay sales (HeatST)
  8. Improve sales funnel conversion (Digital Marketing Blog)


  1. Fantasy football picks (Fake Teams)
  2. Writing screenplays (Entertainment)


  1. Recommend next best learning experience (Forbes)
  2. Personalized learning programs (IBM)
  3. Intelligent tutoring (Forbes)
  4. Provides six trait writing feedback (Hubspot podcast)
  5. Digitized the world’s literature enabling search/analysis (IBM)
  6. Embedded adaptive assessments promotes competency-based learning (Google’s Jonathan Rochelle in Business Insider)
  7. Improve career education (Google’s Jonathan Rochelle in Business Insider)
  8. AI is boosting HigherEd persistence with text nudges (Rose Luckin in Times HigherEd)
  9. Process intelligence tools identify and visualize opportunities (MIT)
  10. Matching teachers and schools (Getting Smart)
  11. Bus scheduling (Getting Smart)

Smart Home

  1. Smart home control systems (Fortune)

Check out these smart home startups. A lot of these use AI behind the scene to get smarter over time.

The Changing Employment Landscape

This has been a weird recovery–sluggish and slow to produce jobs and higher wages. In addition to a bunch of unusual international circumstances, the global economy has been incorporating exponential technology, particularly all the artificial intelligence applications above. While the bots are eating away at some predictable job categories, all this technology has yielded frustratingly slow productivity growth.

The economy remains a head scratcher, but web research yields pretty consistent advice for young people and job seekers in this new age of automation:

  1. Do what AI doesn’t do well: give a hug, solve a mystery, tell a story. (NPR)
  2. Analytical and interpersonal skills will likely become more important. (Brookings)
  3. Focus on adding value in novel situations. (Anthony Goldbloom on TED)
  4. Focus on computational thinking not just coding. (Edsurge)

99. Critical thinking, systems analysis, and inductive reasoning are increasingly important in “mixes and depths” that are currently rare. (Quartz)

100. Social interaction and co-working increasingly important (Business Insider)

  1. Equip graduates to work effectively alongside AI (Rose Luckin in Times HigherEd)

What’s the new hot field? When you pull junior aside at the pool party (like The Graduate), instead of “plastics” you should be recommending “machine learning.”

The first half of the information age was programming computers to do what we want. In the second half of the information age computers are programming themselves. Machine learning is the practical subset of artificial intelligence–the new hub of efforts to add intelligence to every facet of life. And it’s hot.

“It’s huge. It’s really one of the biggest shifts that we have seen in the last few decades. And it’s creating demand, off the charts demand, and this is across all industries,” said Amr Awadallah of Cloudera.

Amr added, “The future need for people with high technical skills when it comes to data analytics, artificial intelligence and machine learning is going to be off the charts.”

More broadly Google’s Jonathan Rochelle knows it takes a smart application of cutting-edge products to help kids learn. He encourages teachers to help kids use the latest products effectively. Those are the skills that will give them the greatest leg up as citizens, Rochelle says. “Imagine if we could teach kids all the tools that are at their disposal,” he says, “and let them take the next step to stand on the shoulders of giants.”