Despite the hype surrounding machine learning and artificial intelligence, many companies still see these technologies as tools of the future. And, while some are too busy worrying about how AI might rob them of their jobs, the brands looking to stay relevant and fresh have adopted these tools to gain a competitive edge. Contributed by ISM Inc.
Leaders recognise that, to survive in this ever-evolving world, their business needs to be where the consumers are every step of the way, and that means integrating technologies that empower and engage employees and customers alike, all while providing the best experience possible.
For those companies that have remained hesitant, change can seem rather daunting. ML and AI represent a new era in business, after all, despite their looming presence in recent years. But, considering how far personal technologies have come within the last decade alone, leaders no longer need to fear the unknown, for these tools are already widespread. Everyday consumers are accustomed to the conveniences of Netflix and Waze, which learn user preferences as they interact with the applications, and with some concentrated investments, brands can enjoy the same predictive benefits at work as they do in play.
While examining the reasons for investing in and implementing ML and AI across the enterprise, it would be wise as well to break down the myths surrounding these technologies. Leaders should not worry that ML and AI will usher in the end of their workforce, for these tools open new doors that will inevitably advance business processes and reduce maintenance costs to improve growth.
With machine learning and artificial intelligence come the rumours of automation. Because these advanced tools can potentially act as substitutes for human labour, those who are not familiar with the intricacies of said technologies often cower in fear, ignoring them at all costs to preserve the business and its employees. Many people are already worried that technology will threaten their livelihood or eliminate their jobs all together. Yet, while the “robots” will likely assume some roles, as people have feared, ML and AI will ultimately create new jobs that are uniquely human, which no computer could ever replicate. In an article published by the Massachusetts Institute of Technology Sloan Management Review, researchers assessed the current environment within companies that have already implemented AI and machine learning systems.
According to the research, three new categories of AI-driven business and technology jobs have emerged: trainers, explainers, and sustainers. Each role complements the tasks performed by cognitive technology in an effort to ensure that the machines remain effective and responsible.
Trainers: essentially teach the technology how to mimic human behaviours. While some algorithms teach the AI to detect the complexities of human communication, other trainers must educate systems on how to show compassion.
Explainers: bridge the gap between technologists and business leaders by providing clarity. When the AI technology recommends actions that go against the norm or when said “smart” tools make mistakes, these explainers must hold the given algorithm accountable and rationalise the result for those who might not understand the technical jargon.
Sustainers: help guarantee that AI systems are operating properly and that any issues are addressed with adequate urgency. Thus, an ethics compliance manager will be integral for companies that still have yet to establish full confidence in the tools they have elected. While these might not be the jobs businesses are used to, these roles open employees to new opportunities for growth. By adapting their current skills for this evolving environment, those who have practically paved the path for these tools will be responsible for keeping AI in line—which means they can rest easy at night. Computers will not replace them during our lifetime, but they will need to embrace flexibility in order to remain fresh and relevant in today’s fast-paced world.
Delaying The Inevitable
Beyond the fears of what machine learning and artificial intelligence could do to the workforce, many leaders have hesitated to integrate these technologies because they regard them as tools of the future. They are still stuck in the “hype” phase despite the fact that ML and AI represent the here and now—they are happening. In fact, International Data Corporation (IDC) forecasts that spending on all artificial intelligence and machine learning systems will grow from the estimated US$12 billion spent in 2017 to US$57.6 billion by 2021.
Coined in 1959 by Arthur Samuel, computer scientist at IBM, the term “machine learning” refers to a computer’s ability to learn without being directly programmed. Therefore, while “artificial intelligence” refers to machines capable of “smart” behaviours, “machine learning” indicates that the given machines can perform without command as computer models come to recognise patterns in existing data and learn to predict the future. Companies that continue to ignore the benefits of ML and AI, however, likely will not be around in the future.
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According to MemSQL, 61 percent of organisations claim that artificial intelligence and machine learning will represent their company’s most significant data initiative in the coming year. Google and MIT Technology Review also teamed up to establish that only 60 percent of organisations are at varying stages of machine learning adoption. Of those companies, 45 percent said the new systems have already led to more extensive data analysis and insights. While 35 percent say they have experienced faster data analysis and increased speed of insight, another 35 percent claim machine learning enhances their research and development capabilities with regard to next generation products.
To remain relevant in today’s increasingly competitive market, companies will soon have no choice but to embrace ML and AI, for these tools are becoming the standard throughout every industry. From manufacturing to health care, organisations that neglect to even consider said tools will find themselves falling behind and becoming irrelevant. While leaders certainly should not jump in and invest without first establishing an effective implementation and integration plan, it is critical that those at the top sit down and determine next steps for bringing these capabilities into their organisation.
Look Into My Crystal Ball
Consumers are already familiar with the predictive conveniences machine learning brings to the table, most notably in the form of Siri or Netflix. Machine learning enables systems to absorb customer data and create accurate, personalised experiences that become more tailored to their tastes as they interact with the technology. Thus, with each movie or TV show the customer watches and rates, Netflix can better assess their preferences and offer improved recommendations based on the connections and patterns revealed.
For companies, however, machine learning and artificial intelligence offer internal benefits that can reduce operational costs and improve organisational efficiency. Manufacturers, for instance, will find that machine learning can predict maintenance issues before they arise, allowing the company to repair their machines before something breaks, as that would cost more in the long run. These benefits also trickle down to the consumer, as ML can predict if something will go wrong with a given product, thereby allowing the company to contact the customer and rectify the situation before the experience turns ugly.
Like all technologies, ML and AI have their flaws, but the benefits ultimately outweigh any of the potential drawbacks, for these predictive insights allow companies to improve operations in ways they never could have prior to implementation. Machine learning essentially enables their computers to become acquainted with their systems and determine the best next steps to take if and when problems arise.
Computer systems almost take on the form of electronic consultants, as they will provide leaders with the guidance they need to grow and improve. Regardless of the myths and mysteries that come along with artificial intelligence and machine learning technologies, these tools are not as scary as they might seem. Much like Big Data and the Internet of Things, ML and AI have become impossible to ignore, for they are integral to the future of business. Leaders try to rationalise their hesitation by claiming that ML and AI are too new, but considering the concept has been around for nearly 60 years, it is clear that these tools have had the time to mature.
Keeping Up With The Joneses
However, those who remain reluctant need not invest in an entirely new infrastructure up front. “Instead, they should focus on tackling the low-hanging fruits that can be improved upon by implementing smaller platforms that carry out basic ML and AI tasks,” says Prem Pusuloori, Chief Technology Officer at ISM, Inc. Yet, while machine learning and artificial intelligence systems represent the future of business, these technologies also embody the present. Those companies that are focused on remaining relevant in the future have already begun to embrace ML and AI today.
Leaders understand that, for continued success, they must not fall behind. They must remain on the cutting edge if they wish to get their slice of the pie. Companies that insist on delaying implementation will ultimately impede growth and, in today’s ever-expanding market, that could stunt progress for years to come.