The Year of Intelligent Apps

Happy New Year!

John Sumser at HR Examiner recently tweeted

Next year's primary software marketing message in #HRTech: "They don't make decisions for me. They make me a better decision maker."

He need not have limited that statement to HR applications. This is the year when the hype around AI will die down. Once again. It has been hyped every few years. Yes, UX will benefit from billions of accents and images we have been training machines on. But we will realize as I wrote here we do not have enough enterprise class data, enough compute capacity or enough talent to train machines across multiple scenarios. Instead, we will realize we do have plenty of data and compute and talent to create intelligent apps for and by humans.

That’s kind of the perspective I presented on autonomous cars in Silicon Valley. I think we are a long way off, but in the meantime as cars get safer with LiDAR and software and accidents drop nicely, that’s a definite reason to celebrate, not mope.

What are intelligent apps? Let me cite a definition, Hasso Plattner of SAP used at SapphireNow. He invoked:

• Intelligent Transactions – automate high-frequency repetitive tasks
• Analytics – make data-driven insights available to everybody
• Collaboration – tap into the collective intelligence of knowledge workers
• Digital Assistant – provide the right answer at the right time

I would broaden the definition. For the last few years social, mobile, and cloud technologies reshaped the look and feel traditional enterprise apps. Now sensor data, automation, blockchains and vertical unbundling and morphing are transforming their guts.

We are starting to see many early examples

a) In many verticals, traditional vendors have not kept up with industry changes even after decades. So, companies are breaking up their monolithic legacy systems and reimaging processes around newer modular applications. Financial Services are showing the way and other industries are starting to look at similar options. Here is just one small example from the financial sector 

“Goldman Sachs, a banking firm that has invested more than $570 mln in fintech companies since 2012. Last year, the banking giant acquired Honest Dollar, a digital retirement savings platform, in order to expand the startup’s brilliant solution to millions of its customers. Along with Standard Charter, Goldman also helped Momo, a Vietnam-based mobile wallet and payment app, raise $34 mln in two rounds of funding. Goldman also launched its own online lending service Marcus last year, a move that is inspired by the fintech culture. The service has so far doled out more than $1 bln in loans and expects to cross $2 bln by the end of this year.”

b) I recently had a chance to be briefed by Aera Technology. While still early in its journey it promises semantic mapping to tens of thousands of ERP and CRM data fields. It has a voice interface. It promises RPA (robotic process automation) to help the work of supply chain, financial and other analysts. Somewhat immodestly it promises “The cognitive technology for the self-driving enterprise. Aera understands how your business works, makes real-time recommendations, predicts outcomes, and takes action autonomously.”

c) Workday has briefed me about its Prism analytics which builds on data discovery tools it acquired via Platfora. The positioning there is “you can bring data in at scale from any source and prepare, analyze, and securely share it with your organization.” (italics mine)

d) Analytics vendors like Anaplan used to be considered for traditional budgeting and forecasting tasks. Now they are helping analysts in CPG and pharma companies with trade promotion and available-to-promise scenarios.

e) Startups like Uptake target unique industry functionality aimed at maintenance and field service of complex industrial assets. Sensors in the IOT generate tons of data – much of it rote and not worth analyzing. But picking up on data points that matter allow the company to boast “Predict which assets will break down. Know the right preventive action to take.”

Analysts will still talk in terms of EAM and HCM and other decades-old TLAs. Vendors will continue to hype about AI. The good news is we are seeing a very different set of intelligent applications take shape.