Until now, our industry has spoken about innovative technologies somewhat theoretically, without providing a clear picture of how these powerful new innovations will be used.
This has left people without a solid understanding of how they will ultimately manifest in our work and personal lives.
That’s starting to change. The application of game-changing technologies is becoming more pervasive and their adoption is growing steadily. In the next five years, they’ll be firmly embedded in many of the core processes and technologies we use. Dimension Data’s new Technology Trends 2019 report explores seven key areas of focus for companies next year. Here are five ways the technology landscape will evolve in 2019.
1. Easier access will accelerate adoption of game-changing technologies
Last year, we predicted that artificial intelligence (AI), machine learning, robotics, and virtual and augmented reality would start to converge to deliver compelling outcomes. Over the past year, we’ve seen this trend coming to fruition and I expect it to accelerate.
One reason for this is an improved understanding of how and where to use such technologies. And of course, we’re also seeing growth in the number of skilled people who know how to leverage them.
Easier access is already accelerating adoption of key technologies
Improved access to such technologies, both from a platform and cost perspective, accounts for another contributing factor for uptake. The hyperscale cloud providers at an infrastructure-as-a-service (IaaS), platform-as-a-service (PaaS), and software-as-a service (SaaS) level – such as Google, Microsoft, Amazon, and Salesforce – are starting to embed these capabilities into their offerings or making them available as a platform to be used by third parties.
This is helping businesses overcome the hurdles they’ve faced in the past. Now they can get access to game-changing technologies without having to invest in their own algorithms and platforms. Instead, they can focus on how to exploit these technologies and speed up the rate at which they get business value.
Bots and robotic process automation are already becoming part of our everyday working and personal lives. It’s relatively simple to create a bot that will access all a company’s sales support systems and provide a consolidated dashboard. These dashboards can be unique to each customer service employee – paving the way for more informed decisions.
2. Identity will emerge as the killer app for blockchain
There’s been a massive amount of investment in blockchain over the past 12 months. In the financial and capital markets, blockchain-based platforms are rapidly starting to dominate. We’re now starting to see this extend to additional settlement areas such as equity trading. There’s also been a proliferation of blockchain-based smart contract platforms across multiple vertical segments, both in the private and public sectors.
Identity management is likely to emerge as one of the killer apps for blockchain in the next three to five years. This is a topic which has never quite been resolved. Most of the major cybersecurity incidents that have occurred in the last few years have involved breaches of people’s personal identity information.
By moving identity management into a blockchain environment, we could solve many of the current challenges and in addition open an entire new value chain, centred on identity. The high levels of encryption and the dispersed nature of data in a distributed ledger are inherent to a blockchain. This immediately changes the level of cyber safety that can be offered, certainly solving one problem.
Other value chains could also emerge, perhaps allowing individuals to truly own and control their identity and its attributes, and selectively allowing the use of such attributes by third parties in transactions or interactions. This could fundamentally change how we conduct financial transactions or even sensitive interactions regarding our health ─ all attributes relating to our identity.
3. Companies will learn how to extract value from data, while respecting privacy
Today, almost every company has access to large volumes of data. But it’s what they do with that data that will define the business models of the future. This isn’t necessarily a new statement, but the context and impact has escalated dramatically. Current business models will be re-engineered by the value of the data that’s generated by existing activities. The value of the data will supersede the value of traditional revenue activities ─ an interesting concept in its own right.
Data monetisation must respect privacy
Ensuring that people’s personal particulars aren’t shared illegally is critical for any business considering this avenue. Regulations regarding data privacy continue to grow, both at a country and at an industry level. Fortunately, the increasing interest in data value management is spurring massive innovation to address the issue of privacy.
Data sources are growing, the granularity of the data itself is improving, and because of this the potential value that can be extracted is growing even faster. The increasing challenge is how to derive insights from disparate and distributed data sources, without infringing regulatory or basic confidentiality guidelines. Anonymised data analytics at scale is an ongoing challenge and we must find ways to gain these rich insights without sharing source data or breaking the law.
4: IoT will change our lives for the better
The number of things connected to the internet globally in 2008 exceeded the number of people on earth. By 2020, it’s expected that 50 billion things will be connected, and this becomes ‘everything’ or simply the internet of everything (IoE). The IoE ecosystem will connect the online and physical worlds in ways we’ve never imagined, and society will become increasingly technology-driven as a result.
There’s not a part of our lives that will go untouched. Automation will take on a new meaning, data value management will be accentuated by the richness of data, and AI will ingest the data to drive intelligent insights and outcomes we’ve never seen before.
The human API will evolve
The IoE will encompass every area of our lives, transforming the way we provide healthcare, and the way we live, work and learn. It will re-engineer our lives through what we increasingly refer to as the ‘human API’, enabling us to interface with various connected systems in ways that are hard to anticipate. The scope of biometrics will expand from what we understand today, to include gestures, emotions, expressions, and many more aspects, triggering automated system reactions to complement, ease, or enhance our activities.
5. Disruption will drive consolidation among tech vendors
The emergence of new technology giants, with very different business models, is driving disruption and shifting the landscape at a scale not seen before. The increasing market dominance of the FAANGs – a term coined to describe Facebook, Amazon, Apple, Netflix, and Google – and a resurgent Microsoft, are key factors.
FAANGs don’t buy their technologies from original equipment manufacturers (OEMs) like HP, Dell, Cisco, or IBM. Instead, they source technologies or components from original device manufacturers (ODMs), write their own code and build their own solutions. This diminishes the addressable market for OEMs. To add a further challenge, these companies are making their source code available in opensource communities, allowing those enterprises that have the resources and funding to follow suit.
FAANGs are simply out-innovating the more established players. Google and Microsoft are embedding advanced innovation into all their products and services, at no additional charge, making it increasingly hard for narrowly-focused technology companies to compete.
A good example is the collaboration stack: companies such as Microsoft and Google provide all the collaboration applications, but include additional functionality such as natural speech recognition, speech-to-text, digital recording, streaming, and fully-programmable interfaces to extend the value chain. This is provided in a consumption-based model – at a fraction of the cost of the more traditional approach, making it tough to match.