AI’s foothold on our lives is looked upon as a supporting tool for intelligence. Not a replacement for human ingenuity, despite decades-long dissent and technological malaise. AI experts agree, the trends on the horizon are pressing. In the short term, the integration of AI into the workforce will create more jobs, though its transition would make some professions in a ubiquitous AI job market, obsolete and outmoded. Written By Kieran McMullen
One of the most commonly used types of AI for business is machine learning: the processing of extensive amounts of data, streamlined through the Internet of Things and connected devices. Machine learning is most effective at identifying trends, patterns and anomalies in data.
Another facet of AI is its deep learning for business application. By using groups of interconnected AI ‘nodes’, linear reasoning can be achieved and utilised. The main difference between machine learning and deep learning, is the former can plateau once certain amounts of data has been captured. The latter, can exponentially improve in performance as more and more data is processed.
The World Economic Forum found that 75% of companies would implement AI in the next five years. Almost 40% of global employment is exposed to AI, including high-skilled jobs. In advanced economies, AI could lean into 60% of jobs, lowering labor demand. In emerging markets, AI exposure is forecasted at 40%, and AI disruption to low-income countries is predicted at 26% in the foreseeable. Many countries falling into the emerging markets and low-income bracket are lacking in the infrastructure or skilled workforces to facilitate an AI overhaul to the extreme.
AI’s potential business scope extends to productivity, the streamlining of processes and decision making. For many businesses, future proofing operations, at minimum, would need to see the use of AI driven chatbots, for conversational engagement and personalised responses. Or, predictive maintenance, using sensor data and machine learning algorithms to predict equipment failures; plus personalised marketing campaigns, harvesting customerdata from habitual online touchpoints.
Enhanced customer experience, in future-proof terms, would see AI-enabled tools for sentiment analysis, with the creation of personalised recommendations, fostering loyalty and customer retention. Augmented reality would feature in the melting pot of AI adaptability for business, plus the use of autonomous decision making, AI-powered cybersecurity, safeguarding businesses against cyber threats, allowing companies to stay abreast of evolving cybercriminal practice.
AI in healthcare has seen innovations in radiology, with the automation of image analysis and diagnosis, assisting in highlighting areas of interest and therefore reducing human error. Other areas AI could aid is drug discovery, patient risk identification and primary care.
AI’s digital right hand is cloud computing, and its no reminder to highlight its importance in streamlining business. A cloud of clouds strategy delivers computing services across the Internet, or cloud. The advantage of using the cloud, is that an organisation only pays for what is used, helping to lower business costs.
Cloud services help organisations handle and act on information rapidly. Globally, many companies are racing toward cloud infrastructure, with forecasts for cloud spending expecting to hit $679 billion. And perhaps more staggering: by 2026, public cloud spending will overshadow 45% of all enterprise IT spending, an increase from under 17% in 2021.
PrivatBank, one of Ukraine’s largest banks, migrated all its operations to the cloud, opting for Amazon’s Web Services (AWS) to shift 270 applications, four petabytes of client data, from 3500 Ukraine-based servers. Back in Britain, Sony adapted remote work setup by using AWS cloud services, helping with the transition of this kind of work, without disruption to productivity, despite the global throes of COVID-19.
Virtually, the cloud’s scalability is unlimited. Infrastructure and hardware costs become redundant, and administrative staffing needs would dwindle. Many companies report significant savings from using the cloud, streamlining Agile workflows, slashing deployment times and simplifying resource management, switching IT costs from fixed to variable.
A responsible, sustainable future for cloud use, might look something similar to Microsoft’s recent advancements in their data centres. Methods like the airside economisation approach improves cooling efficiency, and coupled with Microsoft’s attempts to increase the use of renewable energy sources, could be a way forward for a greener digital future.
In line with the Paris Agreement’s carbon neutrality goals, Amazon have voiced their aim of achieving targets 10 years early, aiming for net-zero carbon by 2040. Google too, have looked at greener practices, using machine learning technology in data centres to boost efficiency, and improve cooling efficiency.
Trends outlined for the future of cloud services, including innovations such as higher adoption of hybrid and multi-cloud environments. By using multiple cloud providers, organisations can achieve higher operational efficiency. Integration of AI and machine learning in cloud services will gain more traction in the future, along with edge computing, speeding up data processing in a local system. Use of edge computing in the future will render firmer security for organisations and save capital.
The demand for cloud computing, according to Gartner, by 2027, is expected to become a key driver for business and the common style of computing. Regardless of size, cloud computing can benefit every business, in storing data, development, and perform other business operations. Statistics from Grand View Research estimate the worldwide public cloud services market is forecast to grow 14.1% from now to 2030.
The quest to build machines that can reason, learn and act intelligently is forthcoming. Just last week, AI models outperformed humans in tests to identify mental states, plus, OpenAI and Google are set to launch supercharged AI assistants, promising to be leaps ahead of tools like Siri or Alexa.
AI-powered technologies in machine learning algorithms and robotic automation are optimising production, minimising downtime and speeding overall efficiency in the manufacturing world. Smart factories equipped with AI-driven systems can analyse vast datasets in real time, creating valuable insights that prevent equipment failures and reduce unplanned downtime.
The AI and cloud services crossroad is an important annal for society and will shift many areas of business. What’s important is to maintain the balance of technological advancement and humane responsibility.
