If there is one thing that the 2020s have never had in short supply, it is surprises. Expecting the unexpected has become business as usual moving through and beyond the global health crisis into an unpredictable new era.
Yet technology has enabled us to weather every storm facing businesses and individuals alike – and looks to be continuing to evolve apace with the needs of modern logistics and enterprise in ways that are both compelling and ingenious.
Moving in tandem, technology and innovation means embracing possibilities as they emerge. With the August 2022 publication of the McKinsey Technology Trends Outlook 2022 report, we can see some key insights into AI, cloud, Machine Learning and more that every organisation ought to lend serious consideration to.
Here are the most incisive technology trends for companies in 2022 – and beyond.
There is no question that the strategic introduction of AI into our working and personal lives has proven altogether transformative. Innovation in this technology continues to accelerate worldwide, yet fortunately the doomsday scenario of a sapient Machine Learning how to overthrow humankind has not yet come to pass.
Instead, more pragmatic applications of AI have become ever more mainstream, both within the SaaS business ecosystem as much as other industry verticals. With demands on every business seemingly escalating by the day, automation made possible through Machine Learning and AI deployment has become a highly active – and contested – space.
The McKinsey report details that 2021 alone saw investment of $165 billion worldwide being proactively mobilised towards applied AI innovation. As one can imagine, the applications for this technology are truly manifold – from more effective strategic decision-making based on highly advanced data analysis, to predictive modelling and classification methodologies.
According to McKinsey, the adoption rate of Applied AI scores four out of five by their metrics – in other words, one step shy of mainstream societal adoption. All at once, it seems our civilisation is ready and willing to embrace the possibilities of Machine Learning and AI for the common good, be that enhanced efficiency or predictive intelligence.
Many industries show interest in Applied AI far outweigh SaaS businesses alone. Aerospace, pharmaceuticals, construction, oil & gas, communications technology and the retail sector are just a handful of industrial sectors actively interested in bringing Applied AI into their operations.
While the likes of Applied AI are enjoying remarkably mainstream attention, the true innovation in Machine Learning technology is happening in more niche verticals, and among more selective – yet influential – interest groups.
Indeed, the McKinsey technology report indicates a score of just one out of five for the Industrialization of Machine Learning, and a global investment figure of $5 billion. Yet it would be remiss and inaccurate to understate the effects that this technology is having as it continues to progress.
Industrialised Machine Learning is a key area of interest for Holocene, and one we believe that both SaaS organisations and a broader range of sectors will come to find fascinating in the coming months and years.
In a true marriage of software and hardware, industrialised Machine Learning focuses on pushing forward the boundaries and capabilities of the technology – but also its level of interoperability.
Every new technology tends to reach the global stage with a litany of potential tools, each of which function within their own ecosystem. In order for Machine Learning to enjoy mainstream adoption, the innovation taking place throughout the sector needs a unified means of interoperability – a more ‘plug and play’ approach for mainstream users and organisations to enjoy.
It’s here that the Industrialization of Machine Learning is playing a pivotal role. This technology trend is already courting tremendous interest in the information and communication technology space – but also the media sector, the automotive industry, in pharmaceuticals and in the aerospace sector.
While the cloud, as a technology, has been with us for many years now – and brought plenty of advantages besides – it surprises some business leaders to learn that its truest potential is yet to be tapped.
Such is the ambition of the $136 billion of investments mobilised in 2021 into cloud and edge computing – exploring the means by which this technology can more effectively benefit not only SaaS players, but everyone connected through technology today.
What is perhaps less known in the mainstream is the term of edge computing, but fortunately its explanation is not a complex one. Cloud computing works by aggregating the technology and resources of vast computer networks, crunching numbers and sifting through data in immense server centres.
Edge computing is an innovation designed to enhance cloud computing by minimising its levels of latency. Edge nodes, as they are called, function by operating geographically closer to the end user, while leveraging the advantages of the cloud for lower-end tasks and functions.
Naturally, the end goal here is speed, agility, accuracy and efficiency – allowing businesses to function with a level of nimbleness that even the cloud enhanced organisations of today cannot imagine.
McKinsey correctly identifies cloud and edge computing as scoring four out of five in mainstream adoption – a technology that benefits almost every industry and vertical on Earth.
Even the most technologically adept reader of today’s Holocene article perhaps cannot fathom the sheer volume of code, networking and interlaced programming ingenuity that has gone into all of the systems, software and hardware to make something as simple as reading this paragraph possible.
Indeed, software development is a vital industry to innovation today, yet also a labour intensive and highly complex one. Creating the breakthroughs in technology that we need involve dedicated teams of experts – and as the old adage goes, the more complex those systems, the more chances they have of failure.
The next generation of software development aims to resolve these issues and enhance software development efficiencies, for SaaS organisations and everyone else besides.
While a niche field of expertise – attracting $2 billion of investment in 2021, and rated by McKinsey as only one out of five in mainstream adoption – next-generation software development is a nevertheless crucial area of innovation.
It aims to produce low-code or no-code platforms for better integration and compatibility, for example – as well as leveraging AI and Machine Learning to automate many of the aspects of software development that can command the most of a given developer’s time and focus.
McKinsey correctly advises that the complications of creating a more egalitarian software development ecosystem – where experienced coders and newcomers in need of a no-code platform can coexist – means solving many technical challenges. However, the rewards if this technology can be mastered promise to be vast indeed.
2022 has been yet another landmark year, and the level of innovation in technology continues to prove inspiring.
At Holocene, we continue to ensure that every new breakthrough is embraced. Our new innovation in industrialising patent-pending Machine Learning technologies is enabling us to help our clients embrace positive change – with our first product promising cloud and AI applications in an efficient, intuitive next generation SaaS solution.