Since the birth of the field at the 1956 Dartmouth Artificial Intelligence (AI) Conference, today’s AI machine learning power inhabits in an entirely new dimension of possibilities. The growing wave of refined AI solutions today can independently master everything from strategy games to new languages.
Modern AI solutions are in all the right positions to make revolutionary changes to the web development and B2B/B2C frontiers. After surveying 2,500 business leaders, PwC reported that 72% of industry decision makers consider AI to be a valuable business asset. PwC also reports that over 60% of business leaders believe that AI is the key to perfectly personalized 1-on-1 buyer experiences.
Several key elements play into the high widespread optimism held about AI and what its full potential may promise. The following are each just some of the most noteworthy things to keep in mind when it comes to AI’s development into 2018 and beyond.
Internet of Things (IoT) and Streamlined Mass Data Adaption
One of the hottest topics circulating in the new tech universe today is Internet of Things (IoT). The advent of IoT promises not only to revolutionize the way that business is done online but even the way that lives are saved during national disasters and criminal incidents; naturally, there’s room here for a bit more predictive power with AI-based machine learning.
Those who say that AI may have a “pretty big” impact on IoT just might be making one of the biggest understatements of the century. Not only will IoT be massively impacted by AI, but many experts project that it will be outright dependent on AI by default. IoT’s benefits are emerging alongside a higher volume of raw data than what’s ever been dealt with before. With higher data comes a more significant challenge to explore and learn from it.
Thankfully, with well-designed AI solutions at the helm, galaxy-dwarfing masses of raw digital information be scanned, learned from and acted upon with superior speed and laser-like precision. Naturally, any AI solution that can flawlessly dive into the deepest depths of the digital ocean and immediately return with the most valuable treasures is ideal for just about everyone.
The primary challenge is not a question of what the most ideal AI capabilities to aim for are, but a matter of figuring out just how to generate the raw computing power needed to match the scale of the task. Developers will be hard at work figuring out ways to make machine learning AI programs capable of “cashing in” on terabytes of data within the smallest possible window of time.
Independent Learning and Preemptive Marketing
In 2014, Timothy Busbice’s OpenWorm AI project culminated in a Lego Mindstorms EV3 robot becoming capable of navigating its environment without any programming whatsoever. With the use of neuron-firing packets mapped to a nematode worm, OpenWorm AI researchers observed their robot moving and pausing just like a nematode worm would with the same neuron activation in nature.
Even without physically lurching forward and pulling backward, modern AI’s environment-reading powers apply to the customer engagement too. Many have already been quietly introduced to the involvement of advanced AI in everyday life through “smart recommendations” on platforms like Netflix, where suggested content is curated based on data from the user’s viewing history.
With further refinement of AI’s power to accurately guess personal preferences based on content engagement patterns, conversions generated from successful preemptive marketing could grow substantially. Rather than just making a machine educated guesses about what movies or shows somebody might like, the perfect preemptive marketing AI solution could automatically generate high-quality content that powerfully resonates with the most narrowly targeted prospects.
AI's Impact on the Job Market
Regarding the potential effect of increased AI investment on jobs, Gartner IT predicts that AI will motivate more employment than it eliminates. According to Gartner's projections, AI should create at least 2.3 million jobs while removing no more than 1.8 million in the process. Should Gartner's forecast turn out to be true, AI implementation will likely create a net gain of just about 500,000 new jobs in the economy before the turn of the next decade.
Because a high number of technology-centric responsibilities will likely be taken over by AI automation, Gartner predicts that just about 40% of IT professionals will hold more diversified skillsets than purely tech-based skills. Rather than making IT staff member services obsolete, Gartner predicts that IT staff members will just become more deeply invested in the strictly business-centric side of their profession than ever before.
Balancing the Creation and Detection of Misinformation
Equally crucial to the valuable content automatically generated through machine learning solutions is AI’s ability to detect and eliminate toxic content. Well-designed machine learning solutions can immediately highlight and deal with many articles about fabricated events that were spun by other AI technologies used for deceptive purposes.
While AI solutions that automatically generate content can potentially invite people with questionable intentions to abuse them, countermeasure production is well underway. Pioneers in the machine learning race are hard at work with ways to make AI content moderation solutions capable of keeping pace with the predictable wave of misleading AI-spun content to come.
In the final quarter of 2017, Forrester Research predicted that the grand total of AI investments would triple before the end of the year. If global AI developers can manage to refine AI to the extent that developers project, then B2B and B2C professionals alike might be able to compensate for the significantly increased level of competition to come.
Tomorrow's AI will present marketers in all verticals unprecedented level of predictive power to determine their most effective approaches to all possible marketing campaigns and web development operations alike. Refined machine learning solutions are not only gaining more raw speed to sift through data with, but also the raw speed to instantly create new rules of engagement altogether.
All in all, the global user data ocean is much more expansive and chaotic than any physical space found in nature; however, with the right machine learning quality, our ability to navigate that ocean is becoming greater than ever before.
(Various Dartmouth Contributors). (2006, July 24). The Dartmouth Artificial Intelligence Conference. Primary reference retrieved from: https://www.dartmouth.edu/~ai50/homepage.html
PWC. (2017, June 22). PwC’s Global Artificial Intelligence Study: Exploiting the AI Revolution. Primary reference retrieved from: https://www.pwc.com/gx/en/issues/data-and-analytics/publications/artificial-intelligence-study.html
Courtney Sato. (2017, October 25). AI and Internet of Things will drive digital transformation through 2020. Primary reference retrieved from: http://www.zdnet.com/article/ai-and-internet-of-things-will-drive-digital-transformation-through-2020/
Gartner Contributors. (2017, October 6). Fake Content to Outpace AI's Ability To Detect It By 2020. Primary reference retrieved from: https://www.mediapost.com/publications/article/308306/fake-content-to-outpace-ais-ability-to-detect-it.html
Gil Press. (2016, November 1). Forrester Predicts Investment In Artificial Intelligence Will Grow 300% in 2017. Primary reference retrieved from: https://www.mediapost.com/publications/article/308306/fake-content-to-outpace-ais-ability-to-detect-it.html