It’s nearly impossible to imagine life without technology and computers. Initially confined to workplaces, computers quickly became ingrained in almost every aspect of our daily lives. With the advent of AI, computers can now mimic human cognitive abilities, such as learning and reasoning, and make independent decisions, just like humans.
Today, businesses are increasingly turning to cognitive technologies to tackle complex challenges. AI is being harnessed not only for business purposes but also to address pressing global issues such as climate change — which positions it as a transformative technology poised to revolutionise the world.
Building blocks of AI
The key tenets enabling the rapid advances in AI we see today are machine learning, deep learning and natural language processing.
Machine learning is a subset of AI that enables a machine or system to learn and improve from experience. Instead of explicit programming, machine learning uses algorithms to analyse large amounts of data, learn from the insights and then make informed decisions, improving their performance over time as they are exposed to more data.
Deep learning is an advanced form of machine learning in which machines learn to decipher complex data patterns. These models autonomously discover and extract hierarchical features, excelling in tasks like image and speech recognition.
Natural language processing focuses on the interaction between machines or computers and human language. This enables computers to read and interpret human languages more proficiently.
AI development is still in its early stages, but its influence can clearly be seen in how it has been integrated with our daily lives. Consider the common practice of unlocking a smartphone using facial recognition. The phone’s camera captures and analyses thousands of invisible infrared dots to construct a detailed map of your face. It then employs algorithms to compare this scan of your face with the stored image to determine whether the person attempting to unlock the phone is indeed you — all in a split second, and all thanks to AI.
More broadly speaking, the integration of AI into business operations enables the establishment of sustainable competitive advantages, which significantly bolsters a company’s capacity and ability to adapt swiftly to evolving market conditions. This adaptive prowess stands as a crucial asset in today’s ever evolving and competitive landscape. By leveraging AI technologies, organisations can cultivate a culture of innovation, agility and continuous improvement.
Three use cases of AI innovation
Organisations seeking to unlock the innovation potential of AI in their businesses should take notice of common use cases. By understanding how and where AI can bring value to the business, organisations are more able to benefit from the immense advantages offered by this powerful emerging technology.
Use case 1 — data sharing
An organisation’s ability to leverage the rich data at its disposal is key to unlocking innovation opportunities that can deliver improved customer experiences, greater operational efficiency and enhanced service offerings.
By analysing shared data, AI systems can personalise product recommendations, marketing strategies and user interfaces, boosting customer satisfaction and engagement. The focus is on how different AI systems or entities can share data sets to enhance their capabilities.
Use case 2 — information exchange
The exchange of information between AI algorithms and connected devices can unlock immense opportunities for addressing important challenges through innovation. Take the example of agriculture, Africa’s largest sector, which employs as many as 226-million people across the continent.
Considering Africa’s vast wealth of arable land and rapidly growing population, it’s vital that the agricultural sector seek ways of harnessing technology to revolutionise food production.
AI-powered drones and tractors can collaborate effectively to oversee and manage extensive agricultural fields, handling tasks such as planting seeds, applying fertilisers and harvesting crops with remarkable efficiency.
In addition, AI can be used to predict weather patterns and enhance agricultural processes. AI-driven weather forecasts can empower farmers with invaluable insights needed to make well-informed decisions regarding optimal planting times, irrigation schedules and harvest periods.
Use case 3 — co-operative decision-making
Consider the example of Africa’s ongoing challenges with energy security. The deployment of AI-driven solutions could help energy companies leverage AI capabilities to create intelligent electricity grids. Here, AI solutions create seamless real-time collaboration between machines and computer systems to dynamically adjust energy generation and distribution based on real-time demand and consumption forecasts.
In this scenario, co-operative and autonomous decision-making, matched with real-time fine-tuning of operational performance, results in a much more efficient — and far more adaptable — energy ecosystem.
As the world navigates the dawn of the AI era, most developments have centred on machines understanding and interacting with humans. The ongoing dialogue between human intelligence and artificial counterparts has been at the forefront, laying the foundation for an age when AI enhances our daily lives, redefines boundaries and introduces a world of limitless possibilities.
However, a pivotal and perhaps even more intriguing facet is on the horizon: the evolution of AI systems that communicate, collaborate and perhaps even negotiate with each other.
Dumisani Moyo is the marketing director at SAP Africa.
The big take-out: AI is being harnessed not only for business purposes but also to address pressing global issues, which positions it as a transformative technology.
This article first appeared in the Financial Mail.