Artificial Intelligence (AI) has quickly become the buzz word of 2017 and looks to be sticking around for the foreseeable future. In recognising the potential prolific impact that AI can have in not only businesses but also in everyday life and social services such as policy development and even emergency services, it becomes imperative that we look at the potential that AI can have in the work environment and also in business processes.
While the potential impact of Artificial Intelligence itself can be far-reaching, the term itself carries little value by today’s definitions. Looking at the many definitions that have arisen from some of the industry’s leading companies, AI may even be, as IBM puts it, Augmented Intelligence. The biggest factor to them reinventing the term is the fact that AI at this juncture is purpose driven algorithms which are capable of analysing a given set of data and identifying the common trends. Some of the examples we are seeing of this form of Artificial Intelligence include Machine Learning which search conglomerate, Google, champions in its voice recognition technology. In addition, we also have the recently launched Bixby digital assistant which does more of the same. This form of AI has also found its space in the banking industry for fraud protection. However, the appearance and application of a true, general AI that is capable of more than just a set of predefined roles is yet to be seen.
Purpose Driven Artificial Intelligence Should Drive Businesses at Every Level
That said, this is the best form of Artificial Intelligence that businesses can implement in their day to day functions. At its simplest, purpose-driven AI can and will drive business targets and also allow businesses to benefit from immediate insights into data that will have taken days and possibly weeks for a data analyst to process. A study from Gartner shows that currently, only 32% of employees have access to Business Insights. However, the business insights derived from these implementations of AI should not only be made accessible to data analysts or top-level management only. In fact, the biggest impact of data-driven business decisions can come at lower levels of management. The potential concerns that may arise from sharing data and insights at every level are vastly outweighed by the potential growth can be achieved from it.
Businesses are, at the fundamental level, being forced to become more data-driven as AI progresses. Business Insights are becoming even more crucial when it comes to analysing, understanding and, in some cases, predicting the outcomes of business decisions. It has also become standard practice to build business models based on data models and algorithms capable of predicting plausible outcomes. That said, not all executives and personnel are able to understand and draw insights from the data that has been meticulously gathered. Implemented AI assists in making sense of the data and visualising possible actions and repercussions of decisions based on quantified models.
Business Insights and analytics derived from the current generation AI allows executives and management to make sense of the data that has been collected without needing to be a data scientist. At the most basic level, the implementation of AI will undoubted allow a better understanding of the multiple facets of the business and allow better, more informed decisions to be made at every level.
The Increasing Need to Regulate Artificial Intelligence
Of course, access and collection of data by AI and companies brings up the question of regulating such activities which need to start not only within the organisation but even beyond at the level of policymakers. However, the evolution and development of Artificial intelligence pose the biggest issue in this respect.
The rapid, constant and ever-changing nature of AI and technology as a whole necessitates a framework of legislation which is able to address current and future issues potentially arising. A luxury which, unfortunately, the current legislators and framework struggle to accommodate. Hence, it will fall to the companies and their conscience to adopt suitable policies that will be able to mould the ethical framework of the implementation of AI in businesses and the use and dissemination of said data.
In Artificial Intelligence We Trust?
Until a time where legislators are able to accommodate the flexibility for the growth of businesses in adopting AI, it will undoubtedly lead to a growing mistrust of the implementation and usage of AIs in businesses. In fact, in a Gartner report, it was found that 55% of people will not consider riding in an autonomous vehicle. This highlights the need for a more transparent system of AI development.
The inherent distrust of AI in society now is, in a lot of ways, a sign of changing times. The increased reliance on AI for day to day life and businesses is disconcerting to a generation who once fantasized about it. It’s natural that the generation now entering the workforce and those climbing the ladder will have a better understanding of AI and the technology behind it.
That said, key decision makers should not be distrusting of the implementation of AI in their businesses. They should cautiously and discerningly look at the implementation of AI in their businesses and look for solutions which cater to their needs.
A healthy distrust of AI and the continual integration of the “human element” into businesses is what will take many businesses into the future. It will be prudent for businesses to remember that data scientists, AI and technology are only part of the equation and look to technology to complement their current strengths: their employees and the skills they offer.
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Mr. Ingelbrecht is a Research Director with Gartner’s Technology and Service Provider Research organization.
Mr. Ingelbrecht has worked in and researched the technology sector for 30 years, latterly focusing on the Asia/Pacific markets from Hong Kong and Australia, where he is currently based. In addition to his work for Gartner, he has lectured on e-commerce policy at Murdoch University, Western Australia. Mr. Ingelbrecht has operated as a Research Analyst and Consultant for major consulting and advisory organizations, and was previously Editor of the Financial Times’ Asia/Pacific Telecom Analyst, and has been involved in numerous telecom, medi and IT research projects, license bids and market studies for industry clients. He is an associate of the Telecommunications Research Project at Hong Kong University and co-author of the books “Telecommunications in Asia” and “Telecommunications Development in Asia.” He has represented Hong Kong at the Pacific Economic Co-operation Council.
Also published on Medium.