Once upon a time in Emerging Technologies

Emerging technologies are defined by Gartner as disruptive with a potential of providing competitive advantage in the marketplace over a 2 to 10 year horizon, but unproven at the time of identification. Every year Gartner analysts using a variety of sources, including industry reports, analyst reports, customer feedback, and vendor briefings, identify and evaluate technologies to create a hype cycle. #gpt3 defines ‘The Gartner Hype Cycle’ as a graphical representation of the maturity, adoption, and social application of specific technologies. It is used to depict the over-enthusiasm and subsequent disappointment that is common with new technologies, and to help organizations make better decisions about when to adopt new technologies. The Hype Cycle provides a graphical view of the maturity of emerging technologies, and helps organizations understand the risks and opportunities associated with each technology.

There are many surprises in the recently released 2022 hype cycle for emerging technologies. NFTs still show on the peak of inflated expectations. Given that the trading volume of NFTs collapsed by 97% between Jan and September 2022, expected this technology to be in the Trough of Disillusionment with a high likelihood of becoming obsolete before plateau.

Second surprise is cloud data ecosystems showing on the verge of slipping into the trough of disillusionment with a timeframe of 2 to 5 years to hit mainstream. The cloud data ecosystem is explained as a cohesive data management environment that supports the whole range of data workloads, from exploratory data science to production data warehousing. I believe cloud data ecosystems are on the slope of enlightenment with a much shorter timeframe to hit productivity across multiple industries. We started our cloud journey more than 3 years ago and through a combination of data warehouses, lake-houses, and data meshes are building robust platforms that aid the implementation of analytics and AI use cases. Surveys by a variety of research organizations point to a similar trend: the combined spending of SaaS, PaaS, and IaaS models is growing exponentially and 81% of all organizations have already adopted a multi-cloud strategy.

While there is an exciting new theme of accelerated AI automation, disappointed that promising AI technologies like PIAI (Physics informed AI) and composable applications that were on the march in 2021 to accelerate growth and sculpt change are missing. They have called out that traditional AI techniques are not able to achieve business adaptability, flexibility and agility and hence the move to autonomic techniques. These are self-managing systems exhibiting three fundamental characteristics: autonomy, learning, and agency. They are projected to hit adoption in 5 to 10 years. 100% aligned on the need to accelerate the creation of specialized AI models, and deploying them to product, service, and solution delivery.

The two other themes this year are expanding immersive experiences and optimized technologist delivery. Immersive experiences combine decentralized techniques and digital humans. SuperApps, that consolidate and replace multiple apps for customer or employee use and support a composable business ecosystem are added to this category. This is a logical extension of the mobile first, disposable app strategy. Optimized technologist delivery seems to be an umbrella theme that builds on enterprise digital transformation. It has technologies that focus on core like cloud, storage, engineering, security, and sustainability.

Looking back a couple of years to see which technologies were identified, and how they fared over the years. In 2020, not surprisingly the technologies were a reflection of a heavily virtual, locked down world, focused on population health. Health passports and social distancing technologies were top of mind and expected to reach plateau in less than 2 years. Biodegradable sensors and DNA computing were on the hype but at the other end of the spectrum, needing more than 10 years to mature. 5 emerging themes were identified,

1.????Digital me: The technologies to watch included health passports, digital twin of the person, citizen twin, multi-experience and 2-Way brain machine interface.

2.????Composite architectures designed to respond to rapidly changing business needs with packaged business capabilities built upon a flexible data fabric. The technologies called out were, composable enterprise, packaged business capabilities, data fabric, private 5G, embedded artificial intelligence (AI) and low-cost single-board computers at the edge.

3.????Formative AI which were models that could evolve dynamically to adapt over time. These included AI-assisted design, AI augmented development, ontologies and graphs, small data, composite AI, adaptive ML, self-supervised learning, generative AI and generative adversarial networks.

4.????Algorithmic trust: Algorithmic trust models that would ensure privacy and security of data, source of assets and identity of individuals and things. These included, secure access service edge (SASE), differential privacy, authenticated provenance, bring your own identity, responsible AI, and explainable AI.

5.????Beyond Silicon: New advanced materials making technologies faster and smaller to overcome the physical limits of silicon, aiding critical technologies like DNA computing, biodegradable sensors and carbon-based transistors.

In 2021, health passports and social distancing technologies dropped off the radar while decentralized technologies and NFT landed right on the top of the hype cycle promising to hit plateau in 2 to 5 years. The digital twin technologies consolidated into digital humans, while clouds diverged into niche categories. Three themes emerged,

1.????Engineering trust to establish security and reliability, built on repeatable, proven, scalable and innovative working practices. The as-a-service offerings were at the core of this theme.

2.????Accelerating growth took the baton from the earlier digital me theme forward and leveraged interactive, AI-driven representations that behaved in “humanlike” ways supported by a range of technologies including conversational UI, CGI and 3D real-time autonomous animation.

3.????Sculpting change: Hurting from the impact that Covid 19 had on businesses physics-informed AI was of particular interest. This targeted creating a flexible representation of the context and conditions in which systems operate, requiring developers to build more adaptive systems leading to robust and adaptable business simulation systems that are reliable in a wider range of scenarios. Other emerging technologies in this theme included composable applications, composable networks and influence engineering.

Much to learn from, much to experiment with, and so much to gain.