The global pandemic pushed many businesses to fully embrace digital transformation at pace, spurring an environment of innovative problem solving and creativity.
We have seen the technology industry innovate on a huge scale at impressive speed in recent years, as it serves to meet the demands of a post-Covid world. But now as we continue to move into a ‘new normal’, what big innovations can we expect in the tech landscape this year?
From AI-generated art to chatbots, here are seven predictions from our global technology experts on what they expect to see develop this year.
The recent unveiling of OpenAI’s new artificially intelligent chatbot, ChatGPT, which went viral across the internet, is an amazing insight into the transformative potential AI has. OpenAI’s new model has been trained to interact with humans in a conversational way, making it possible for ChatGPT to ask follow-up questions, challenge incorrect statements and even admit its own mistakes.
Just as the industrial revolution transformed industries and societies, the AI revolution is impacting how we now live our lives. We have already witnessed a turning point in AI’s development, where the technology successfully moved from proof of concept (PoC) curiosities. Businesses now understand if an AI-based project will be successful or not and embed powerful features into everyday tools.
This year, we are going to see the impact of AI become more and more embedded in our everyday lives, both personal and professional. Whether it’s copywriters increasing output and pace by using AI generated content, through to AI assistants making human-like calls to book your personal appointments for you, AI will be a common feature in our day-to-day activities.
Platform engineers create an improved user experience and add business value by building curated self-service layers that deliver speed and process agility. They will become standard in software engineering organisations who will establish them as internal providers of reusable services, components, and tools for application delivery. These teams will be particularly impactful when it comes to building cloud-based platforms with industry-specific functionality to address specific vertical requirements.
I’m expecting to see the adoption of service mesh technology, a dedicated infrastructure layer that controls how different parts of an app communicate with one another, steadily increase over the next year. This technology enables app optimisation by allowing extra capabilities, such as observability and zero-trust security, to be added to an application without requiring changing the code.
Technologies such as the open-source project Istio Service Mesh are becoming more established in the industry as a solution to managing and securing large amounts of microservices. There are also some exciting developments in the service mesh space due in 2023, such as the sidecar-less Istio ambient mesh, which will provide broader application compatibility and reduce infrastructure cost as well as fuel further adoption.
Undoubtedly, technology is making the world a better place to live. However, the technologies we use to make positive changes can also be turned against us. AI-generated images are current examples.
Over 2022, many high-profile data breaches were reported in the media, which included consumers’ identity data. The main danger of breaches is not that data is compromised but it creates a sea of information in which everything can be found. If a malicious actor wants to change their identity, all they must do is find data of individuals that fits their needs and generate the identity document by using a combination of AI image-generation algorithms.
We will certainly see this type of fraud increase this year, so it is critical that businesses are partnering with identity verification and fraud prevention companies such as GBG to provide multi-layered protection to make fast and accurate decision on identity and transactions.
Effectively addressing the issue of creating responsible and trustworthy machine learning (ML) applications first requires a realistic understanding of what ML truly is. ML is too often hyped up as emerging “artificial minds” on the path to out-thinking humans. In reality, today’s ML applications result from the same classes of algorithms that have been under development for decades but implemented on considerably more powerful computers and trained on larger data sets. In other words, ML algorithms are “mind tools,” not artificial minds.
Successful applications of ML hinge on more than big data and powerful algorithms. A crucial factor to ensure these algorithms are responsible, fair, unbiased, and trusted worthy is human-centric ML. We will see this continue to develop throughout 2023.
Businesses have already started to automate parts of their workflows to save time and resource. This is currently more prevalent in technology companies, but I expect to see this continue and evolve out into wider industry verticals in 2023.
Hyperautomation is the next step. This is a process of linking and verifying multiple automated journeys and processes, increasing consistency and speed. This will enable businesses to cut costs, free up IT resources and improve the customer experience – critical wins in the backdrop of today’s economic landscape.
As consumers, we’re all getting used to sending our picture or recording a video to help confirm our identity virtually – many neo-banks, such as Revolut, require this for opening a new bank account, for example. However, as technology becomes more available and usable, so does the chance to exploit it.
With the creation of this new verification method there are also people hard at work finding a way to crack it. Deep fakes are one of problems in this space. As this fraudulent activity increases, I expect verification and prevention technology to flourish, extra layers of verification to be considered such as further biometric verification checks to the images and recordings as well as verifying the actual device used to capture the video rather than just the imagery itself.
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