Knowledge Economy: Six Disruptive Influences of Artificial Intelligence

Knowledge Economy: Six Disruptive Influences of Artificial Intelligence

The world has gone digital. In fact, we are approaching the Fourth Industrial Revolution, also described as Industry 4.0: an age in which a range of new technologies is expectedly fusing the physical, digital and biological worlds in addition to impacting all disciplines, economies and industries.

This is an age marked by emerging technology breakthroughs in a number of fields, including artificial intelligence, robotics, augmented reality, nanotechnology, quantum computing, biotechnology, The Internet of Things, 3D printing and driver-less vehicles, among others.

One of these emerging technologies, Artificial intelligence or AI, as it is commonly referred to, has the potential to cause significant disruptions to many established industries, presenting amazing new ways for business leaders and individuals to simplify complex tasks.

According to the Research and Development Unit of Yudala, Nigeria’s fastest growing e-commerce outfit, here are six ways Artificial Intelligence will shake up things in the corporate world.

1.Double-edged impact on jobs and employment opportunities: Artificial intelligence promotes the growing reliance on machines which possess the ability to perform a wide range of physical and cognitive tasks, admittedly with more efficiency and accuracy. This poses a great deal of concern for the future as these machines may put many jobs at risk and ultimately reduce human employment. While these concerns are legitimate, research posits that the rise of artificial intelligence and automation may, nevertheless, have a double-edged impact on employment: negative and positive. In the negative sense, AI may displace humans by directly replacing them in tasks previously performed by these workers. On the positive side, the deployment of machine learning and artificial intelligence may end up increasing the demand for labour in other industries or create new jobs or openings as a result of automation.

2.Data analysis and presentation: With the emergence of machine learning which is a direct off-shoot of artificial intelligence, the task of crunching numbers, analyzing data and presenting this as useable information just got easier. A single supercomputer using artificial intelligence running on continuous machine learning will definitely out-perform the work of ten or more humans working with spreadsheets to analyze and interpret the same amount of data. Most machine learning apps have the capability of, not only analyzing huge amounts of data in record times, but also reducing errors to the barest minimum –  a factor that makes them logically preferable to high-cost and error-prone human accounting or consultancy teams.

3.Budgeting: Closely related to the foregoing is the refinements and research-backed approach to the process of budgeting which AI lends. For most businesses, budgeting is often carried out haphazardly on a yearly basis, with funds allocated in similar patterns to various activities and business units. This inadvertently results in a situation where certain business units get more working capital while other units which yield more returns struggle with the meagre figures allocated to them. By deploying artificial intelligence, business leaders can generate valid information on the performances of various business units and gauge more accurately the returns on the investments made on specific activities. This will potentially cause a major overhaul of existing budgeting systems used by corporate organizations and bring more value and objectivity to the entire process.

4.More personalized marketing: The exciting benefits of artificial intelligence will also be keenly felt in the field of marketing, as advances in the field will usher in landmark advances in the marketing value chain, leading to more personalized experiences for consumers. Through AI tools, marketing will assume an automated dimension, enabling companies to deliver a richer, more personalized experience for all classes of consumers and resulting in stronger connections between brands and consumers. Ultimately, these new approaches will build brand affinity/loyalty and positively impact bottom lines. Presently, a number of organizations are deploying artificial intelligence principles to simplify the processes involved in various branches of marketing including email marketing, SEO, mobile, social media, among others. Global e-commerce giant, Amazon, is playing a leading role in this aspect –  a step that is on the verge of being replicated by Yudala – by relying on a series of algorithms to determine what customers are likely to buy or require next, with these suggestions and creatives sent to the target customers via customized emails in a process that is entirely automated.

5.Recruitment/Human Resources: AI will radically transform the recruitment and human capital management function by infusing more objectivity and transparency into the entire process. This will equip business leaders or owners with the requisite insight to take more informed decision on hiring, compensation, promotion and gender pay disparity/biases in the work-place. By leveraging the benefits of advanced statistical tools and machine learning, AI can help organizations recognize and reward performance more objectively among the entire work-force through the detection and elimination of partiality, imbalances and subjective appraisals.

6.Banking and finance: The entire financial services sector will also be disrupted by the emergence of artificial intelligence solutions and applications. A recent research survey carried out by The Economist revealed that 49% of banking executives believe the traditional transactional banking model will be dead by 2020. Through AI, banks, insurance companies, asset/wealth management firms and capital markets will have a plethora of cutting-edge tools that will streamline and bring unimaginable simplicity and ease to their core financial processes and customer service offerings. The potential is limitless. Robo-advisors are being mooted in the sphere of asset management; banks will expectedly rely on chatbots to boost customer experience while other AI tools will simply thorny reconciliations, reporting of earnings, financial analysis and asset allocation, among others. AI will also help insurance firms process claims, streamline their processes and uncover fraud. Understandably, a number of financial institutions are awake to this reality, head-hunting and mopping up fintech talents, in a sort of arms race to ensure they are not left behind in the sweeping wave of tech-mediated changes that is afoot in the sector.

 

 

WHAT IS ARTIFICIAL INTELLIGENCE

Artificial intelligence (AI, also known as machine intelligence, MI) is intelligence exhibited by machines, rather than humans or other animals (natural intelligence, NI). In computer science, the field of AI research defines itself as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of success at some goal. Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”. AI research is divided into subfields that focus on specific problems, approaches, the use of a particular tool, or towards satisfying particular applications. Artificial intelligence is not one technology but rather a group of related technologies – including natural language processing (improving interactions between computers and human or “natural” languages); machine learning (computer programs that can “learn” when exposed to new data) and expert systems (software programmed to provide advice) – that help machines sense, comprehend and act in ways similar to the human brain.  These technologies are behind innovations such as virtual agents (computer-generated, animated characters serving as online customer service representatives); identity analytics (solutions combining big data and advanced analytics to help manage user access and certification) and recommendation systems (algorithms helping match users and providers of goods and services) which have already transformed the ways in which companies look at the overall customer experience.