The Fourth Industrial Revolution – digital transformation – is progressing. Last week Gartner hosted their annual gala of CIOs and tech titans. This year the rise of artificial intelligence, decline of IT specialists and big tech reincarnation were among the top predictions. Unlike last year, this time there were few surprises and a subdued tone. Let’s delve into several of the Top 10 Gartner future forecasts.
Gartner Reveals Top Predictions for IT in 2018 and Beyond
Slow Death of the IT Specialist
Gartner repeatedly emphasized the need for technologists to transform into roles that grow revenue for the business. Per Gartner guestimates, “By 2021, 40% of IT staff will be versatilists, holding multiple roles, most of which will be business, rather than technology-related.” By 2019, IT technical specialist hires will fall by more than 5%. IT technical specialist employees will fall to 75% of 2017 levels. They went on to say in 2018 and beyond CIOs will be more accountable than ever for revenue generation, value creation, and the development and launch of new business models using proven and emerging technologies.
For as long I have been in technology, I was taught to help the business. From building data warehouses and reporting solutions as an implementer to building and selling solutions as a vendor, it has always been about the business. How does what my team is working on help make money, save money, and so on.
The change I sense is coming to IT and technology pros is getting out of the server room or “coder cave” per se into blended roles within the business. For analytics professionals, most of us have already been integrated within lines of business to positively impact the bottom line. That has been historically and remains to be our job in the future.
Big Tech Reincarnation
Last year Gartner inferred that big tech would dominate the world. This year we are certainly seeing more concerns being raised from media, government officials, and other leaders about anti-trust and oligopoly power in the digital era. In Europe, we are seeing legal actions and massive fines being levied on tech giants.
An oligopoly is a market with limited competition. A small number of firms enjoy a large majority of market share. An oligopoly is similar to a monopoly, except that rather than one firm, two or more firms dominate the market. For an educational, entertaining overview of oligopoly dynamics, watch Jon Oliver’s recent episode on this topic.
One of the forecasts this year is Gartner’s big tech self-disruption. This year Gartner says, “By 2020, five of the top seven digital giants will willfully “self-disrupt” to create their next leadership opportunity. The top digital giants include Alibaba, Amazon, Apple, Baidu, Facebook, Google, Microsoft, and Tencent. Examples of self-disruption include AWS Lambda versus traditional cloud virtual machines.” This forecast did not surprise me – it was already happening. Several big tech vendors are reinventing themselves. They are entering new industries, cannibalizing on-premises apps to expedite customer migration to highly profitable cloud models, expanding bundled offerings wider across channels and adding data monetization models to seize more customer wallet share.
Artificial Intelligence and Machine Learning
The mega-hot topic of the event was artificial intelligence. I literally just wrote about this for InformationWeek – Artificial Intelligence Today: Time to Act. Everywhere you look, artificial intelligence is being discussed. New artificial intelligence companies are popping up and pilot projects are being launched to embed intelligence into applications, reports and business processes.
In 2017, 85% of surveyed executives in an Accenture study cited intent to invest extensively in artificial intelligence related technologies over the next three years. Per CB Insights, a record $6.5B of capital has been deployed across 650+ deals in 2017, already surpassing the $5.7B deployed across almost 1000 deals in all of 2016. Talking to one of Gartner’s top analysts in this space at Tableau Conference, I learned artificial intelligence was discussed in 95% of the 1:1s at the Gartner Symposium.
Artificial intelligence will change the world as we know it. For IT and analytics pros, artificial intelligence will change the types of tasks and jobs that we do in the future. I love what I am seeing in ETL, data preparation, feature engineering and automated insights powered by artificial intelligence. The grungy work is being improved by artificial intelligence. It also saves time and reveals hidden patterns in masses of data that would not be feasible to explore manually.
I love what I am seeing get “intelligently automated” in the areas of ETL, data prep, insights and feature engineering.
At the event, Gartner said “In 2020, artificial intelligence will become a positive net job motivator, creating 2.3M jobs while eliminating only 1.8M jobs. By 2020, AI-related job creation will cross into positive territory, reaching 2 million net-new jobs in 2025.” Honestly, I am skeptical of those numbers. I have not seen the detailed reports on how they arrived at those estimates.
Other artificial intelligence prediction stats include “Global IT services firms will have massive job churn in 2018, adding 100,000 jobs and dropping 80,000” and “By 2021 Gartner predicts, AI augmentation will generate $2.9T in business value and recover 6.2B hours of worker productivity.” This last quote is compelling and why I see augmented analytics powered by artificial intelligence to be a must-have in your analytics arsenal. Augmented analytics does not replace but rather supplements what you are doing today with traditional BI and modern BI or visual analytics.
The newer generation of augmented analytics solutions are wonderful investments that will generate immediate returns for you. This is my favorite area of the analytics industry right now. I have several articles and webinars to help you get started with it.
Natural Language User Experiences (UX)
Natural language generation (NLG) is a subfield of artificial intelligence which produces human language, natural, human-sounding sentences, statements, or paragraphs from data. It generates analytic output with contextualized narratives. Unlike Natural Language Processing (NLP), an ability of a computer program to read and understand text or human speech, NLG writes human language.
In the information age, humans interacted with machines by typing, pointing, clicking, and viewing a screen. Soon, machines will be controlled with human gestures and voice via NLG. I am convinced natural language user experiences will be one of the most significant advances to revolutionize UX and “humanize” apps.
For analytics pros, I expect natural language to empower anyone to easily ask data-related questions and get answers in real-time. Conversational interfaces simplify complexity for the masses. We are just starting to see next generation natural language capabilities from Narrative Science and Sisense, Automated Insights and TIBCO Spotfire, Tellius, IBM Watson Analytics, and many other vendors that are powering analytical search, voice, bots, contextual graphs and metric performance interpretation.
Repeating the same message from earlier this year, bots are hot. Gartner is predicting by 2021, over 50% of enterprises will be spending more on bots than mobile app dev. We already see bots widely used for technical sales and support. Robo-receptionist, robo-lawyer, robo-cop and even robo-bartender recently were released into the unpredictable human world. These initiatives will continue to expand and improve with cognitive intelligence that we see with Hanson Robotics Sophia.
That wraps up my annual Garter Symposium summary. Next up…Tableau Conference 2017