Artificial Intelligence, Machine Learning and Digital Transformation in Business
There is a real fear among workers worldwide that Artificial Intelligence (AI) could take most of their jobs in the near future. If you work as an ad executive, AI is likely to take your job. If you are a taxi driver, AI is definitely going to take your job within the next few years. If AI doesn’t take your job (and it probably will) you are definitely going to get less pay because of its advances.
Indeed, the Organization for Economic Development (OECD) estimates that 9% of the jobs in its 21 countries are threatened by automation. Other estimates say up to a quarter of the global knowledge workforce could become automated just over the next few decades. New reports continually add to the list of the soon-to-be-jobless, saying that AI is going to steal work from lawyers, writers, and even information technology experts building and installing computer systems today.
The term ‘Artificial Intelligence’ was first coined in 1956, but it is in these 2010’s that the term has taken on a more realistic world-use form with the advent of concepts that were unimaginable just a decade ago. Self-driving cars, intelligent kitchen appliances and humanoid robots show how far AI has progressed. The disruptive nature of AI is being increasingly felt due to the accelerated pace at which AI is developing thanks to advances in machine learning.
While there have been some shifts in key concepts and methodologies, Machine Learning (ML) applications are nearly fifty years old and many people mistakenly use the terms AI and ML interchangeably although they are two entirely different concepts. Artificial Intelligence describes a state where machines can work with little or no human input. Machine Learning is when machines learn to take on new tasks without being programmed to do so, but by depending on algorithms they have worked with. Deep Learning is a recent addition to machine learning methods that’s driving ML applications into different areas of human life. It’s based on learning data representations, as opposed to task-specific algorithms and getting more commonly used due to the abundance of data and the increase in infrastructure availability, capacity and affordability.
Artificial intelligence and machine learning are at the heart of digital transformation where automation is increasingly taking over human tasks in different business processes and tasks. With the advent of the internet and easier global communications at the turn of the century, business organizations became more global in their operations but till recently still managed from central offices. Artificial intelligence coupled with cloud storage has changed all that. Organizations are now handling operations in different parts of the globe in decentralized ways using artificial intelligence in processes such as logistics and warehousing, where production is done in different parts of the world using the least cost analysis.
While AI may still not able to perform common sense tasks efficiently, AI systems are proving more efficient than human brains at processing huge data volumes. The Internet of Things, Social Media Networks, and business Big Data Analytics are just some fields where AI is changing the way business operations are carried out. AI applications in business will become more widespread as machine learning capabilities get even better. Whether they will be able to take human jobs that lend themselves to automation is no longer a question of if but really of when as AI/ML gains currency. Emerging trends that underpin this point include…
- destruction of installed software as a concept when software learns how to react to different scenarios using its own algorithms and so replaces the need for software updates. This has been observed in business processes like customer service where Customer Relation Management (CRM) systems are getting smarter in responding to different customer actions without human input.
- increase in contactless services to the customer by using AI in analyzing data collected from the customer at different contact points like mobile apps and websites as business look for ways to get leaner and reduce operating costs. Using AI, for example, banks are now able to offer customers a mortgage when the customer views different properties on a website.
- improving location-based services that deliver targeted marketing messages depending on where the customer is located, and what he/she is doing as higher competition forces businesses to go wherever customers can be found. Thanks to AI/ML changing marketing as we know it, a shoe company can invite its customer into the store with an offer to try out a new shoe as the customer walks past one of its stores, a restaurant can now show the day’s menu to its customers in the vicinity.
AI applications in business can only get better and more efficient in the future, meaning even more disruptions are expected in a wide variety of business processes. Some of the constructs AI/ML is using to dominate the digital world are…
Search Engines are the pioneers in the use of machine learning. This is because web users will usually input search terms in natural language, expecting the search engine to figure it out. With each search, the search engines improve their algorithms enabling faster searches and more relevant results.
Chat Bots go beyond the typical interactive voice recognition. Chatbots are increasingly being used by organisations to improve efficiency in customer experience while maintaining human-like contact. This is for tasks like changing passwords, account balance enquiry, menu orders and so on.
Recommendation Engines analyse customer data collected from different contact points like websites and mobile apps. The data is then analysed for customer behaviour, tastes and preferences for the most appropriate service/product to be put in front of the customer by email or SMS. It is standard practice for shoppers on big retailers like Amazon to see carefully selected products that are closely related to what they have been looking at. Follow-up emails also land in the inbox with recommended products from time to time.
CyberSecurity Bots study malware algorithms and data patterns, enabling them to flag other malware that matches these patterns and adapt to different cybersecurity threats and becoming better at thwarting cyber-attacks. Large organisations see thousands of threats per day, which would be overwhelming for any human analyst.
AI will have a significant impact on product offerings in the technology, media, financial services, professional services, and telecommunications industry over the next five years as AI accelerates new product and service offerings and the Business Process Outsourcing (BPO) of these industries. More powerful hardware and more versatile programming languages means smarter machines being deployed in more and more fields for both profit and non-profit organisations. The IDC forecast that spending on cognitive and artificial intelligence systems will reach $57.6 Billion by 2021.
While human input may not be entirely eliminated in the near future, smarter machines are certain to dominate many aspects of business and technology in the near future.