From yesterday’s ground-breaking AI innovations to tomorrow’s Metaverse, technology is advancing at a never-before-seen rate
With new developments fighting for priority in today’s modern tech stack, the challenge for leaders is to identify what advancements are relevant today and which are still in the realms of fiction for the foreseeable future.
First on the agenda; solid foundations for complex clouds
Whether companies call it digitisation or transformation, the vast majority of organisations are moving everything to the cloud at pace. Multi-million-dollar initiatives manifest in myriad cloud configurations from multi to hybrid, answering many challenges. However, having heavily invested a large number of resources into cloud transition, fewer organisations prioritise the subsequent phases that ramp up cloud return.
These subsequent phases provide the foundation for cloud ROI – improving operations, forecasts and predictions using ML and data science for revenue. Hyperscalers build products that drive all kinds of business cases, but the benefits cannot be realised without a sound foundational cloud. Getting a handle on today’s complex cloud initiatives must be a primary priority for any future-focused organisation.
Don’t hesitate on ethical AI
With the growing list of consumer-facing AI applications, there have been greater calls for transparency and mounting pressure on businesses to consider responsible AI before developing or deploying new initiatives.
This is particularly true in the wake of Covid-19, which heralded a leap in AI deployment. Post-covid-19, 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.
Companies are still in the early days of controlling AI algorithms. The first step is to define parameters- what does the company want to follow from an ethical and non-biased perspective? Once these parameters have been defined, the algorithms and outcomes must be constantly checked and adjusted to avoid the bias seen in some AI applications.
The 5-year plan; intelligent automation
Technologies such as Robotic Process Automation (RPA) have made inroads over the last 5 to 10 years. However, RPA abilities have been limited to mundane automation tasks. For example, looking 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, the rise in intelligent automation, combining technologies like AI and RPA, is increasing the work automation can do to relieve humans of process-driven tasks.
This isn’t to say the human element becomes inadequate; human decision-making skills are still vital in these processes. But, 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 potential of NLP
Natural language processing (NLP) is the fastest developing area of AI and automation, rapidly developing alongside other burgeoning technologies to create new paradigms. For example, NLP combined with conversational AI will enable very different interactions with clients and 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 already being used to help customers shop with humanoid avatars, providing an optimised user experience whilst mitigating the effects of the current labour shortage. However, we are yet to see its full potential. In the future, NLP will become integrated with everyday life, allowing us to communicate with machines and programs in similar ways that we do with other humans. And, when combined with developments in biometrics, these machines like humanoid robots will eventually acquire the ability to read body language and facial expressions.
An ‘almost’ virtual reality
The Metaverse is the latest advancement to enter the hype cycle. Currently, the idea is hype and not a priority for many organisations. However, in the next five to ten years, there will be a dramatic investment into the digital world – especially in the consumer sector – and things we would not even imagine two years ago are already a fact of life today.
The Metaverse’s true potential will come to life when the younger generation, who have grown up as digital natives, become consumers. With the help of conversational AI, this generation of consumers will be able to interact in a meaningful way with humanoid avatars, chatbots and digital agents. As it stands, the Metaverse is a long way off for us. However, it will be the reality for the next generation of consumers.
Making this virtual reality world feasible is a leap, but a realistic one in the long-term.
About the Author
David Semach is EMEA Head of AI & Automation at Infosys Consulting . Infosys Consulting is a global management consulting firm helping some of the world’s most recognizable brands transform and innovate. Our consultants are industry experts that lead complex change agendas driven by disruptive technology. With offices in 20 countries and backed by the power of the global Infosys brand, our teams help the C-suite navigate today’s digital landscape to win market share and create shareholder value for lasting competitive advantage.
Featured image: ©Photocreo-Bednarek