From yesterday’s ground-breaking automation innovation to tomorrow’s Metaverse, the pandemic has led to a slew of rapidly advancing technologies. While these are all fighting for priority in today’s modern tech stack, the challenge now is for business leaders to identify which needs the most attention right now, and how these technologies will develop.
From NLP to intelligent automation, ethical AI to the Metaverse, what tech realities should be garnering brainpower today, and which are still in the realms of fiction for the foreseeable future?
Laying the foundations for complex clouds
The vast majority of businesses are transitioning to the cloud at incredible speeds as part of their digitisation or transformation programmes, manifesting in myriad cloud configurations from multi to hybrid. However, having invested time, money, and energy into cloud transition, fewer organisations capitalise on subsequent phases that build-up opportunities for cloud return.
Once the foundations are in place, cloud data analysis can improve operations, forecasts and predictions using machine learning and data science for revenue. Hyperscalers build products that drive all kinds of business cases, but the benefits cannot be realised without a sound foundation. Getting a handle on today’s complex cloud must be a key priority for any future-focused organisation if real change is to occur.
The potential of ethical AI
With multiple real-world and future uses for associated technology, AI is often lauded as a panacea for business problems. However, before creating or deploying AI, organisations must determine how to do so properly and responsibly. Post-pandemic, a large portion of operational activities will be executed by AI, enabling teams to focus on higher-value tasks.
However, with greater scrutiny of tech practices and calls for transparency, businesses must manage the deployment of smart AI while ensuring privacy safeguards, preventing bias in algorithmic decision-making, and meeting guidelines in highly regulated industries. The main ethical challenges of AI fall into four broad categories; digital amplification, discrimination, security and control and inequality.
Controlling AI algorithms is still in its infancy for most businesses. However, the first stage is to identify parameters: what does the company want to follow from an ethical and non-biased point of view? Following the definition of these criteria, the algorithms and outputs must be regularly evaluated and adjusted to avoid bias.
While the hype of AI in itself is beginning to level, problematic AI is a hot issue. Ethical AI, therefore, isn’t a question for tomorrow but a serious consideration for today.
What lies in the future for intelligent automation?
Technologies such as Robotic Process Automation (RPA) have made inroads over the last 5 to 10 years. However, the potential of automation has been limited. For example, let’s look at the HR challenges of recruitment or the supply chain process of demand forecasting and planning. A small fraction of these critical processes can be automated using technologies like RPA – perhaps just 10%.
The remaining 90% cannot be automated by leveraging legacy capabilities. However, combining intelligent automation with technologies like AI and RPA is increasing the work automation can do to relieve humans of process-driven tasks.
Human decision-making skills are still crucial in these processes. As part of long-term strategies, organisations would do well to start making moves to incorporate intelligent automation across business units, laying the foundations for the next generation of automation which is undoubtedly on the horizon.
The promise and capabilities of NLP
Natural language processing (NLP) is the fastest developing area of AI and automation, evolving at an incredible rate with other emerging technologies to usher in new paradigms. For example, NLP combined with conversational AI will enable very different interactions with clients and with employees.
NLP can help to drive sales and increase revenue, whether that be through the use of chatbots, translation tools or grammar correcting technology. NLP is the heart of software tools that consumers use daily and is already being used to help customers shop with humanoid avatars, providing an optimised user experience whilst mitigating the effects of the current labor shortage. However, we are yet to see its full potential.
In the years to come, NLP will eventually become more integrated into everyday life, allowing us to communicate with machines and programmes similar to how we communicate with other humans. And, when combined with developments in biometrics, machines like humanoid robots will eventually acquire the ability to read body language and facial expressions.
A not-quite virtual reality
The Metaverse is the latest advancement to enter the hype cycle. Currently, the idea is not an absolute priority for many organisations. However, in the next five to ten years, there will be a dramatic investment into the digital world, especially given the acceleration of digital tools resulting from Covid. Things we would not even imagine two years ago are already a fact of life today.
The reality of the Metaverse will come into play when younger generations’ enthusiasm and engagement for platforms such as TikTok translate into consumer spending power, allowing brands to thrive in the Metaverse. Hand in hand with this comes conversational AI, as interaction with humanoid avatars, chatbots and digital agents starts to happen in a meaningful way. We are already seeing companies start to invest in the enabling capabilities that will deliver the promise of the Metaverse in the years to come. Making this virtual reality world feasible is a leap, but a realistic one.
Right now, the Metaverse is our science fiction. But for the generations of the future, this will be their virtual reality.
