AI in Industry

Automated systems act autonomously and perform tasks with little to no human involvement in the process.

Automation can boost efficiency and productivity by streamlining high volume repetitive tasks; reducing opportunity for human error and operational, training and IT services costs. Introducing elements of automation can add value where humans truly excel, such as relationship building, creative thinking and leadership.

The true gains of automation are not achieved by replacing humans with machines. Instead, it is achieved by recognising what each is innately equipped and gifted to perform and leveraging the synergies between the two to create better outcomes for humans and business.

Make predictions based on trends and patterns in current and historical data; using available data to make predictions about unavailable data to inform future decision making.

These insights help businesses better anticipate and prepare for different conditions and scenarios. Combining predictive analytics with human expertise and experience helps business leaders make better strategic and operational decisions.

Leveraging the power of predictive analytics is key to becoming an insight-driven organisation. Predictive capability will become a key differentiator and source of competitive advantage, an invaluable tool in your business intelligence arsenal as a means to helping organisations make smarter decisions about an uncertain future.

Pattern and anomaly detection involve sifting through vast amounts of data to discover patterns and trends - and anomalies that are the exception. The nature of anomalies depends on the context, but the pattern is an unusual or unexpected case that offers new insight into your data.

Possessing this capability enables your business to identify potential risks, threats and opportunities that are too complex for a human to spot amongst the size, variety and speed of big data.

The potential of anomaly detection is that allows your business to identify outliers and initiate measures necessary to identify and automatically respond to avoid or mitigate potential risks and threats or develop a strategy to exploit a potential new opportunity.

Hyper personalization is the evolution from a one-size-fits-all approach to one that tailors communications, service delivery and experience to the individual customer. That means applying insights into customer’s needs, interests and behaviours and into every interaction, engagement and touchpoint.

Customers are coming to insist on personalised experiences. They expect every engagement to be customer-centric; reflective of their individual needs and helping them seamlessly discover products and services that benefit them.

The business case for personalization is clear: to remain relevant, brands must personalize experiences and outcomes to the customer level. This shift can increase brand loyalty and build a long-term relationship with customers rather than a transactional one.

A key barrier to human-machine interaction has been the inability of machines to effectively understand and respond to our primary communication method, speech.

NLP enables machines to understand the intent, meaning and sentiment behind language and respond . This allows humans to communicate with machines in a similar way to how humans interact with each other.

If machines can reliably interpret and translate between languages in real-time, this would unlock world-changing opportunities for global business.

With its potential to revolutionise numerous aspects of our lives and how we interact with machines and one another, this is an area that businesses should be proactively exploring.

Goal Driven systems are often used in scenarios when humans do not know or cannot explicitly programming a machine to perform a task due to its complexity; requiring machines to learn and discover themselves.

The machine acts and learns through repetition and analysis of error and success the optimal set of actions that progress it towards achieving its goal.

Made famous by defeating world champions in chess and Go, these systems have evolved and are at the forefront of world-changing applications such as robotics and drug discovery; helping humans solve problems at an unprecedented speed and scale

The amount of data at our fingertips is increasing exponentially. This is the problem of big data; the volume, variety and velocity of data creation exceeds the capability to manage and leverage effectively.

A key challenge is that most data is unstructured. Photos, videos, music, voice recordings, text and handwriting; whilst these make sense to humans, machines struggle to extract meaning. This is because such data is rarely formatted in a way that readily allows machines to extract insight.

Machine learning is overcoming this limitation and creating new possibilities by structuring data sets to make them useable and helping us solve complex problems once the sole responsibility of humans.