Machine learning is taking over the running of many industries. To some, it's a sound of rather bad news while to other businesses, its a sign of better days ahead. We know some entrepreneurs have embraced or had experience with machine learning thus we asked them what they think will be the impact of it on business.
#1- Time and money saving
Machine learning can change more than you might think at first blush. In fact, it's already helping me save thousands a month. I taught a machine to read the dozens of incoming requests from media that come in three times a day and to share with me only those that might interest me. If I were to read them all myself, it would take roughly an hour a day to filter through them and I'd been paying a PR firm to do that, among other things, for me. Now the machine does it, with about 90% accuracy, and I'm freed up to only see the best inquiries. The funny thing is that none of this was difficult, nor do I know how to write a single line of code. As machine learning becomes more accessible to all of us (and understood by all of us), the changes in how we work will be tremendous and largely positive. The machines can free us up from low value, low reward work and allow us to focus on the higher end of the value chain.
Thanks to Jim Tobin, Carusele!
#2- Increased productivity
Modern IT environments are incredibly (and increasingly) complex and ever-changing, leading to large amounts of time and resources devoted to monitoring, troubleshooting and course correcting. It’s a reactive position for most companies, but when teams use AIOps technology they can leverage change-tolerant algorithms and access indexed information. This allows them to spend more time focused on proactive, meaningful work rather than fixing the same problems repeatedly or spending time managing rules and filters.
Thanks to Phil Tee, Moogsoft!
#3- Competiton for high skilled human capital
To most people, machine learning equates to artificial intelligence (AI). And when they think AI, they think about robots. It's not the nice ones, like Rosie on the Jetsons, but the warped ones, like HAL in 2001: A SpaceOdyssey. The negative AI narrative was heightened with the ongoing debate between Elon Musk and Mark Zuckerberg, with Musk carrying the banner for fear. There’s a reason for this: the power of fear of the unknown. The introduction of AI and Big Data bring both feelings of strategic opportunity, as well as the burden of the unknown to an executive team. A bigger and real related threat for businesses surrounding AI may just be the reality of reconciling competition for human capital as a result of technology. As the prevalence of AI, data and automated processes continues to grow, it appears that the highly skilled human component is more and more important – ironically and thankfully. As I see it, is that the more powerful and complex technology becomes, the more important highly skilled workers are for an individual organization, as well as throughout the value chain of technology production and usage. The upshot? The already competitive marketplace for human capital will only continue to heighten in the near future, and businesses need to strategize today regarding how they will attract and retain these highly sought after employees.
Thanks to Adam Goldberg, Torchlight!
#4- Meeting of more complex demands
The machine learning and big data based AI that currently pervade are powerful tools for identifying associations in large quantities of data, but don’t have much on humans in terms of working out the complex phenomena of cause and effect, or to identify modifiable factors that can engender desired outcomes. So how does AI make the leap to the next step? The first step is to enhance the big data and machine learning with another layer of AI functionality – that of cognitive intelligence. What is missing in the AI learning simply from crunching the data at hand is an AI that can reason through and incorporate missing information, reason abstractly, plan, and problem solve. Mapping out scenarios and searching for potential outcomes to weed out confounders or even fill in missing data gaps through hypothetical scenarios. In real world application, it is substantially more complicated that reasoning through an opponent’s potential moves in a complicated game and altering game play to reach a desired outcome. But the foundation is there, and the technology is certainly there as well. While machine learning and big data has dominated for years, a new breed of commercial AI has begun to emerge to meet the more complex demands of modern human machine interactions. The aim of cognitive intelligence AI platforms isn’t to supplant big data or machine learning. Rather, it’s there as a supervisor of sorts, monitoring how traditional AI process data, filling in gaps and identifying misinterpretations. Ultimately, the goal of a cognitive AI platform is to be able to complete tasks without the need for human supervision, to be able to quickly process unexpected or unfamiliar external input and adjust its response accordingly.
Thanks to AJ Abdallat, Beyond Limits!
#5- Speed up the data processing
Machine learning is showing up in almost every type of industry, from manufacturing to customer service and retention. That's why it will be important for employees to have adequate training at becoming machine interfaces in the coming future. This type of interface is necessary for machine intelligence to be effective. Humans will still be responsible for what actions need to be taken as well as how to interpret the outcomes. Machines will simply speed up the data processing part so that we can have more time and space for creativity.
Thanks to Lindsey Havens, PhishLabs!
#6- Simpler online marketing efforts
Machine learning is changing the landscape of marketing and SEO. Consumer interactions will be more simple and instantaneous as companies further integrate the use of this technology into their online marketing efforts. For marketers, AI is helping professionals fully realize personalization and relevance at scale. Platforms like Search and YouTube have the ability to reach billions of people everyday, so marketers can utilize AI to reach their target and focus on the right demographics on a larger scale.
Thanks to Tyler Riddell, eSUB Construction Software!
#6- Both bad and good
What machine learning will mean is convenience, and overall that is a good thing, generally. However, it may also mean a decline in our ability to articulate. When Big G can understand what we mean better than we can articulate it, that does seem to be a bad thing for us as a species. If we trust machines to think for us, that thinking capacity may begin to atrophy. However, it also means that for any business smart enough to harness the power of rank brain, they'll have an easier time getting their message in front of relevant customers, making it easier and faster to grow their business – and even less wasteful to advertise.
Thanks to Justin West, Hundreds of Customers LLC!
#7- Ethical concerns
A little more than a year ago, we started talking about machine learning and AI as a way to improve data protection technology and simplify data management tasks. A year ago we suggested that AI-powered technology would gain momentum in 2017, but again, we didn't expect the scale and the speed with which AI-driven solutions would penetrate every industry. It was quiet a year ago, but in 2018 it's part of every organization dealing with data. The widespread adoption of AI technology brought about some ethical concerns. Driverless cars, drones, AI-driven applications and the potential to affect the world's economies, citizens, and the internet has raised a philosophical question of whether AI is going to change the world for better or worse. This debate has people like Tesla's Elon Musk saying on one hand that AI will be a threat to people, and then we learn that Tesla is working on its own autopilot AI chip. The conflicting messages are typical given the AI rush that the industry is experiencing in 2018. We stand at the threshold of an exciting time.
Thanks to John Zanni, Acronis!
#8- Extraction of meaningful information
Machine learning is going to have a profound impact on business over the next decade. The clearest case is in investment decisions. We previously didn't have the computational power to handle the massive amount of data that is constantly being produced. But we're finally at a point where we can extract meaningful information from the noise. As an example, picking a location to start your business will likely be a largely quantitative question rather than a qualitative one.
Thanks to Neel Somani, UGBA 198!
#9- Training of the workforce
One of the less obvious areas in which machine learning will have a huge impact is training of the workforce. Generally, training is still one of the more conventional practices in businesses. In recent years we have seen some improvements with the help of online learning platforms, video tutorials, digital handbooks, etc. But in order for a true revolution to happen in the space of education, we needed an extra dimension. Today, we are at the dawn of such a revolution, thanks to machine learning and artificial intelligence we are able to look at training, and even education as a whole, from a whole new angle. Machine learning can identify both the talents and the areas of improvement for individuals. Thanks to artificial intelligence, hyper-personalized training can be provided, assisting the employee where needed. These continuous learning efforts will boost the skills, talent and outputs of our people to unprecedented high levels. Already today, companies that are leveraging machine learning for training purposes are accelerating the human potential.
Thanks to Tom Pennings, Onsophic Inc.!
#10- Technical expertise will become obsolete
Non-linear thinking has always been an asset in business. Thinking globally and outside the box or seeing the big picture are clichés rooted in truth. As we enter the era of automated automation, these abilities are the key advantage we'll (presumably) maintain over exponentially learning machines. Technical expertise will become obsolete more quickly. It's still unclear how this plays out for workers and businesses; and on what timeline. It seems likely, however, that opportunities and success will follow for individuals and enterprises that can best perceive, anticipate, strategize, and adapt.
Thanks to Anthony Glomski, AG asset Advisory!
#11- Efficient running and better customer engagement
Machine learning has become a necessary fabric that must be woven into the modern business. I have seen machine learning dramatically influence businesses both in their customer engagement strategies and their business operations. One way it is already making an impression is in leveraging existing data to better engage customers resulting in higher quality leads, better customer service and an improved sales process, ensuring a higher win-rate. Business operations are also being impacted and machine learning is enabling businesses to run more efficiently. For example, it is already helping to predict performance issues with equipment, reduce false positive alerts or enable better management of inventory for many forward-thinking businesses. Of course, this is just the tip of the iceberg when it comes to machine learning's impact on businesses. In 3-5 years, it will be even easier to deploy and implement, and the results will speak for themselves.
Thanks to Katherine Kostereva, bpm'online!
#12- Provision of more user-tailored services
As a successful startup in the recruiting space, machine learning will allow us to better tailor our offerings to meet the specific needs of our client companies and job candidates. Imagine a scenario where one company prefers accountants with 4 years of experience and another 2 years for the same exact role. Over time, a computer analyzing this data will pick up on these company-specific trends and highlight them to the recruiter. The same goes for the candidate side, as we place more and more candidates we can determine the company benefits that candidates value most. Machine learning will never replace the human touch in our industry but it will allow us to provide more tailored service to our users.
Thanks to Akash Srivastava, Vested!
#13- The Excitement & Opportunity
Once every few generations, truly remarkable transformations happen. As an entrepreneur I have often looked back on the period of the industrial revolution and wondered how exciting it must have been as engineers, scientists and entrepreneurs were just learning to harness the incredible power of machinery. The opportunities were endless, and the competition was spirited and vibrant. The foundation of so many wonderful businesses were established in this era. Artificial intelligence and machine learning will create a similar wave of opportunities for those who can imagine the applications and uses of these amazing technical capabilities. And like the industrial revolution, the impact on society will be just as profound.
Thanks to Paul Dlugosch, Natural Intelligence Semiconductor!
#14- A number of ways
Machine learning is the biggest opportunity to augment human abilities. Finally, we have tools that can find connections in massive amounts of data, never forget important details and can work 24/7. All areas of business will be significantly reshaped in the next 3-5 years. Even now we can see how Machine learning solves seemingly unbreakable problems in medicine, improves decision-making practices, automates online ads placement and even helps plan better events. The challenge for humans is only to be able to keep up with the pace that we now set for ourselves.
Thanks to Maksym Podsolonko, eazyplan!
#15- Focus on core competencies
In the office setting, sophisticated ERP systems are already using machine learning technology to predict project roadblocks and use aggregated data from completed projects to flag when a program or workflow is veering off course. As this technology continues to mature, AI and machine learning tech will also allow employees to more easily complete manual and repetitive tasks, such as automating and streamlining data entry, expense reporting and purchase orders. Overall, AI and machine learning will enable skilled office workers to spend more time focusing on their core competencies over the mechanics of maintaining data. On a larger scale, employing digital bots means financial costs are lower, and time is saved on tasks usually spent on manual operations or classifying data.
Thanks to Claus Jepsen, Unit4!
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