There is no doubt that artificial intelligence is the future of the world, and it will eventually seep into our lives in all sorts of ways. AI will drive the economy of tomorrow, and if properly harnessed it can generate enormous prosperity for humanity and take us all to the next level. In short, AI is being used to create an upgraded world.
No wonder AI skills are amongst the most in demand, and AI predictions for 2020 is one of the most searched topics today. Everyone wants to stay updated and connected with its innovations to have an edge in this fast-paced system. However, you have to know the past and understand the present to be prepared for the future. Hence we will start with the evolution of artificial intelligence before delving into why AI is essential.
The evolution of artificial intelligence
It might have started as fragments of imagination long before, however the Dartmouth Summer Research Project on Artificial Intelligence was a seminal event for artificial intelligence as a field. In 1956, Dartmouth College professor John McCarthy coined the term artificial intelligence and organised an intensive summer workshop bringing together leading experts in the area.
The next notable event in AI was when computers got their first voice. ELIZA, developed at MIT by Joseph Weizenbaum in 1966, was perhaps the world's first chatbot. ELIZA could not talk like Alexa, but communicated through text.
It took time, and there were multiple experiments and successes in between. But the rise of useful AI happened in 1980, when Digital Equipment Corporation's XCON expert learning system was deployed, and by 1986 it was credited with generating annual savings of $40 million. The rollout of smart machines into business had begun, and by 1985 corporations were spending $1 billion per year on AI systems.
Fast forward to 2012, when the power of deep learning was unveiled: researchers at Stanford and Google explored unsupervised learning, which accelerated the pace of AI development and opened a new world of possibilities in building machines to do work which until then could only be done by humans.
Soon after, in 2015, machines started identifying better than humans. Researchers declared that computers could identify objects in visual data more accurately than humans for the first time.
The next most significant leap in the history of AI in business was in 2018, when self-driving cars hit the roads for the first time after successful testing. The launch of Google spin-off Waymo's self-driving taxi service in Phoenix, Arizona, was the event. Another notable surprise came from Google in 2018 when they unveiled Duplex, an addition to the Google Assistant which could make calls on behalf of a user and perform tasks such as booking restaurant tables and hair salon appointments.
Who is bringing AI to life
The pace of AI evolution took the fast route in recent times, and numerous attempts are being made to get it mainstream, quite successfully. Here is a set of entities that have been making phenomenal progress in bringing AI to life. They were recognised in the 2019 AI Breakthrough Awards programme, as winners for the best AI based solution in the following categories:
- Advertising: AdTheorent
- Cybersecurity: ExtraHop
- Customer service: LivePerson
- Workforce management: Kronos
- Manufacturing: FogHorn Lightning
- Marketing: Criteo
- Retail: Axonify
- Best predictive analytics solution: IBM Watson
- Best overall AI based analytics solution: Cognizant, Xtreme Data Engineering
- Best overall AI based analytics company: Absolutdata
- Best transactional bot solution: Mya Systems
- Best chatbot solution: Verint
- Best AI solution for big data: NetApp ONTAP AI
Having said all this, we foresee AI bringing in a new era in 2020. The emergence of smarter tech is the visible next level, where informed decision making through empowered computer algorithms is becoming the critical business differentiator across industries. Gartner predicts that the business value created by AI will reach $3.9 trillion in 2022. As AI becomes more capable of analysing and interpreting data faster, businesses will build better, more personalised and profitable campaigns.
The various progressive levels of artificial intelligence
It is clear that we are sitting on the cusp of AI innovation, and for a more in-depth understanding it is necessary to break it down further. Beyond this point, AI will progress from assisted intelligence to augmented intelligence and finally autonomous intelligence. Let us look at the three forms that exist today.
- Assisted intelligence
- This is a widely available level of artificial intelligence, which makes your existing task more manageable by assisting you, that is, taking over a lot of repetitive and standardised actions. Customer service chatbots, and the Gmail algorithm that sorts your mail into Primary, Social and Promotions, are a couple of examples.
- Augmented intelligence
- This is still an emerging technology that is taking AI to the next level. Unlike assisted intelligence, this form augments or enhances the task being performed by humans. Augmented intelligence focuses on enhancing human knowledge rather than replacing it. Current uses include personal budgeting assistants and the algorithms that enable ride-hailing cab businesses.
- Autonomous intelligence
- This is the future of artificial intelligence, where machines will be able to act on their own, practising complete autonomy. Imagine self-driving cars, doctorless hospitals, or robots making their own music. Implementing technology where human interaction or decision making would not be required at all would depend mostly on the amount of trust we are willing to put in these solutions.
When enterprises reach a stage where they have to consider introducing AI across various functions, the question they have to ask is which level of AI they choose. Do they want assisted intelligence that automates monotonous work? Do they want humans and machines working in collaboration, making decisions with augmented intelligence? Or do they want to hand over all the decision making to machines that use autonomous intelligence?
Artificial intelligence in business functions
Though there is a growing buzz around artificial intelligence, business leaders are still not exactly sure where they could apply AI to benefit their functional units. This is not surprising, as embedding AI across the business requires significant investment in talent, technology and organisational transformation. While applications of AI cover the entire range of functional areas, specific use cases let us identify the most significant impact it can have.
- AI for business insights
- With the assistance of AI activated predictive analytics and data based insights, businesses can benefit in multiple ways, such as lower costs, better service quality, and being proactive in anticipating market risks.
- AI in marketing
- Marketing is one function that has already been at the forefront of evaluating, testing and applying AI to predict consumer behaviour and make product recommendations. AI has tremendously empowered marketers with the ability to identify, understand and know their target consumers.
- AI in sales enablement
- There are multiple methods through which machine learning can offer recommendations on actions that businesses take to boost their sales channels. AI enhances the capability of sales data and establishes the much-needed connection between a customer's intent and revenue pipelines.
- AI in procurement and supply chain
- Smart contracts, where procurement systems are truly autonomous, are the future of strategic procurement. With the influx of AI, tasks like automated buying, AI assisted vendor sourcing, and intelligent chatbots that provide instantaneous insights and support are becoming a reality.
It would be wrong to stop here and say these are the only areas where AI can be embedded and harnessed. AI's impact and penetration are becoming stronger every moment, and there are and will be numerous use cases.
In line with this thought, we at Research NXT take pride in announcing our first ever research on AI in the coming year. The two areas we will focus on are AI in marketing and AI in procurement. We will also be interviewing industry experts to get their best practices around AI enablement for better business results.