Artificial Intelligence: Types and Applications in Business
What is AI really?
There is a lot of hype around AI (artificial intelligence) these days. Firstly, AI is very far from what we see in sci-fi movies, whether the cute robotic boy looking for his human mother in Steven Spielberg’s 2001 film or the villainous sentient spaceship computer HAL 9000 in Stanley Kubrick’s 2001: A Space Odyssey. Business leaders need to understand: What is AI? What are its current capabilities and how can it be used to add value to business?
Artificial intelligence refers to a wide-ranging number of activities that attempt to simulate human thinking and problem solving capabilities using computers and machines.
AI – Different types & categories
Several types of AI can be defined according to capabilities and functionalities. If we think of AI as a spectrum, on one side is the narrow or weak AI, which has more or less already been achieved. On the other side of the spectrum, we enter into the speculative area – artificial superintelligence or computer self-awareness. Different writers distinguished different types of AI – but generally, the split is between narrow/weak AI and general/strong AI.
Artificial Intelligence
- Type 1
- Narrow AI
- General AI
- Strong AI
- Type 2
- Reactive Machines
- Limited Memory
- Theory of Mind
- Self Awareness
Narrow AI / weak AI
Narrow AI uses machine-learning to carry out specific tasks. Machine learning is the most common type of AI being used in the business sector today. Machine-learning focuses on giving software applications the ability to “learn” – or gradually improve in a way that mimics human abilities.Machine learning can solve problems beyond the capacity of the human mind. Machines can be programmed to identify patterns and relationships within massive data sets. Using “learning” algorithms, machines can be trained to improve their data recognition and organization abilities.
General AI (strong AI)
Artificial General Intelligence has not yet been achieved. It remains a theoretical construct. While Narrow AI can be used to respond to specific situations such as developing viewer recommendations or replying to customer queries, General AI should be able to apply generalized intelligence to any issue, in any domain. A General AI machine would be able to understand the world as well as a human does and would be able to learn to carry out a huge number of tasks. As an example, a chatbot using General AI would be able to carry on a conversation with a customer using NLP (natural language processing) without being limited to standardized query/answer scripts.
Super AI (strong AI)
Artificial Super Intelligence is still purely speculative, implying a future where there are machines which are capable of exceeding human intelligence, possessing thinking skills of their own.
Uses of AI in business
AI technology has enormous potential to transform many different sectors such as health, sales, HR, operations and manufacturing. Some of the areas where AI can improve business performance include:
- Personalization – enhancing customer experience throughout customer journey
- Targeted advertising/promotions
- Targeted product recommendations
- Virtual customer agents
- Process automation
- Preventative maintenance
- Robotic process automation
- Productivity increases
- Ramping up manufacturing outputs using AI and robotics
- Data analytics – one of the most commonly used AI applications
- Increasing data processing capacity and efficiency
Some real-world examples of AI include:
- Siri, Alexa and other smart assistants
- Self-driving cars
- Robo-advisors
- Conversational bots
- Email spam filters
- Netflix/Facebook/YouTube recommendations
AI benefits & risks
IBM’s 2021 Global AI Adoption Index revealed that businesses are accelerating AI adoption. 30% of IT professionals surveyed report that their business is currently using AI, and over 40% say that their company is speeding up AI rollout due to the Covid-19 pandemic. While AI is becoming more accessible there are still challenges in the lack of AI skills and increasing complexity of data.
There are many actual and potential benefits of AI including streamlining operations and increasing efficiency. When dealing with huge volumes of data, using AI can reduce human error and provide valuable business insights. But AI is still an evolving technology. There are many high-profile examples of AI “failures”, including:
- IBM’s Watson for Oncology Project canceled after Spending $62 Million: a review of internal project documents found that the Watson supercomputer recommended wrong cancer treatment advice
- Apple’s iPhone Face ID Fail: Security concerns were raised after a Vietnamese security software firm claimed to have “tricked” iPhone X’s Face ID feature using only 3D-printed masks.
As the case when implementing any new technology, businesses need to invest in the following:
- Developing an understanding of AI tools, methodologies and current versus potential capabilities
- Investing in training/recruiting employees with AI knowledge
- Selecting the appropriate tools to address specific business concerns
- Cascading an AI strategy throughout the company – getting executive and staff buy-in
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