Enterprise Tech 2021 Predictions—A Curated Sample

Over the past 1-2 weeks our research team has scanned many, if not all, of the enterprise technology predictions and trends for 2021, across cloud, data, analytics, machine learning, networking, ops, semiconductor, security, privacy, and other domains. Below is a curation of quotes with the source authors and publications. Our primary takeaway: it is an incredible time to be in enterprise technology.

• Just as you’re unlikely to see ‘Office proficiency’ in resumes today, you’re unlikely to see ‘data proficiency’ by the end of the decade. (Sudheesh Nair, ZDNet)

• The output from citizen developers using no-code will outpace that of traditional IT teams by 2022. (Josh Caid, Enterprisers)

• 90% of large global companies will have a chief data scientist in place by 2022. (Ira Cohen, Datanami)

• Enterprise workers will interact with live or recorded video more often than written communication soon. (Upal Basu, SV Business Journal)

• "Everything as Code" will be the evolution of the as-code paradigm, and Infrastructure as Code will expand in other DevOps areas. (Aliaksandr Liakh, DevOps Digest)

• Edge is the new cloud. The number of new operational processes on edge infrastructure will grow from less than 20% today to over 90% in 2024. (Dave McCarthy, IDC)

• FOG computing will be the big buzzword of the year. (Jack Wallen, TechRepublic)

• 75% of work conversations will be recorded and analyzed by 2025. (Kasey Panetta, Gartner)

• Voice Assistant as a Service will be a new buzzword in the in-app market, with simpler and more developer-friendly abstractions. (Kumar Rangarajan, VoiceBot)

• While SASE has become a hero product, it won’t be replacing SD-WAN or on-premises security, at least not in 2021. (Tobias Mann, SDxCentral)

• GraphQL and JAMstack will continue to see adoption with developers and will penetrate enterprises in 2021. (Sudipto Ghosh, AiThority)

• The regulatory environment will mean 2021 will usher in "The End of the Wild West of Information Sharing." (Balaji Ganesan, ZDNet)
• Our understanding of climate science will accelerate by using ML to sift through vast amounts of data and model the future more accurately. (Werner Vogels, Fast Company)