Discussions about artificial intelligence (AI) and cognitive technologies tend to revolve around grand concepts, be it attempting to discover significantly more galaxies than ever before or making a healthcare system much more efficient.
But within businesses, a quiet revolution is underway where companies are gaining access to these tools that don’t just promise significant improvements in the long term, but within the short term as well.
It is worth bearing in mind, however, that it is common to lump AI and cognitive technologies together, even though the way they work is vastly different. To help differentiate between the two and explain what these technologies mean for businesses in the short term, Deloitte’s director of data and analytics, Michael Ennis, is on hand to explain.
Do businesses and organisations know the difference between cognitive technology and AI technology?
There is certainly a blurring of the distinction between the two, and with good reason – they are both on the spectrum of ‘automation’.
Cognitive specifically refers to a set of technologies that can perform and/or augment specific tasks, develop more informed decisions, and create interactions that have traditionally required human intelligence and cognitive behaviours, such as planning, information processing and continuous learning. These would include technologies such as robotic process automation (RPA), machine learning and voice/speech recognition. In simple terms, cognitive technologies are designed to augment or complement human intelligence (eg replicating actions using rules-based judgement).
AI is the next level on the automation spectrum and describes technologies that are designed to mimic or replicate human intelligence, requiring much more complex, human-like thought processing and thinking, such as emotion and logical reasoning.
What are some of the greatest data problems that Deloitte aims to help solve?
Deloitte are working extensively in the cognitive and AI areas with a broad range of clients to solve many problems, but most problems take one or all of the following forms:
- Automate or eliminate some organisation ‘processing’ activity such that we can better leverage our workforce to do more meaningful, value-add activities.
- Leverage our internal, external, structured and unstructured data sources (customer data, product data, channel data, GDP data, demographic data etc) and provide real insight for our customers.
- Explore all technologies that can reduce the reliance on human intelligence alone and move to an operating environment that utilises a combined set of skills and capabilities to deliver the best outcome.
Aside from finance, what other sectors is Deloitte working with cognitive and AI technologies in?
Deloitte works with a broad range of clients across the public and private sector. Here are a few examples:
- Public sector: We are working with a public sector organisation to pilot chatbot technology to support a more automated support service for customers and businesses.
- Manufacturing: We are working with a large manufacturing organisation to implement RPA technologies to monitor supply chain activities across their organisation and create more real-time inventory management.
- Medical services: We are working with a medical services organisation to provide voice/speech (tone and intonation) recognition technology.
- Insurance: We are working with a global insurance provider to implement a series of interactive machine-learning technologies to proactively interact with customers to guide them through a claims submission process, to drive greater efficiency and a smoother customer experience.
- Hospitality: We are working with a global hospitality network, leveraging blockchain technology to streamline the booking process and provide greater transparency on accommodation availability across multiple regions in real time.
Are some businesses hesitant to work with these technologies?
Many organisations are running established proofs of concept and many are seeing the benefits of implementing cognitive or AI technologies in their business.
In a recent Deloitte survey of 250 ‘cognitive and AI-aware’ leaders, 76pc expect cognitive and AI technologies to “substantially transform” their companies in less than three years.
There are also a number of factors that are compelling organisations to take action. These include an exponential growth in the volume, variety and velocity of data; faster processing speeds and smarter algorithms enabling higher machine performance; and growing customer expectations for omni-channel, personalised propositions and ultra-engagement, similar to Netflix.
How do you foresee these technologies developing in the next three to five years?
This is difficult to predict, but what is most certain is that cognitive and AI technologies are here to stay, with adoption rates increasing every year.
There will be many more successful adoptions of cognitive technologies, particularly at the lower complexity end of the automation spectrum, but we will also see advances in more complex technologies like blockchain, which will in time revolutionise many industries, such as financial services.
What advice would you have for any organisation looking to use cognitive or AI technologies in the short to medium term?
- Do your research. Become more familiar with the technologies and capabilities that are most relevant for your sector/industry.
- Examine your organisation. Look across your organisation and identify a number of functional areas and processes where cognitive and/or AI technologies might deliver commercial, operational or customer value.
- Be prepared to fail, but fail fast. Many organisations are now running two-speed environments where one side operates a ‘business as usual’ environment, with the other side operating a ‘fintech’ environment. Here, new propositions, products and distribution methods are being tried, tested, failed and retried. It’s all about continuous innovation.
Not every organisation can be an Apple, but many can be a Samsung!
The post Confused about cognitive and AI tech? Here’s what businesses need to know appeared first on Silicon Republic.