At it’s most basic level, artificial intelligence is a computer programming technology that learns, adapts, and performs tasks without any human input. It’s able to mine and extrapolate data intuitively and make adjustments or recommendations based on that data. AI is already being used by even the smallest businesses to cut costs and improve customer service.
The simplest demonstration of this technology is the chatbots that pop up on the corner of your screen when you visit an eCommerce website. They’re able to interact with visitors, answer questions, and resolve issues, providing a more meaningful user experience. Industries from health care to travel to financial services are recognizing the value of AI technology and incorporating data science to impact the way they do business, improving our overall productivity and quality of life.
The Future with Artificial Intelligence
Imagine a world where shops can anticipate your needs and send an SMS to your phone, alerting you to personalized discounts on products while you shop. Where the very room you’re in can sense your mood and respond with the right lighting, sound, and temperature. Cars and public transportation will detect road conditions in advance and adjust accordingly.
As technology advances, programming becomes more intuitive. Outcomes can be predicted faster and with more precision. It is a future where doctors can pull up your entire medical history and diagnose any illness as easily as checking a message on their smartphone, with an accuracy never before imagined. It’s the future imagined by Alan Turing back in the 1950s, and it’s finally here.
Big, Big Data
Current trends indicate that by the end of 2018, 6.4 billion devices will be connected across the globe. The amount of data generated by smart sensors this year will reach 400 zettabytes. To give that figure a little context, one zettabyte = 1,180,591,620,717,411,303,424 bytes of data. Extracting and parsing that amount of information into something meaningful, accurately and without taking years to do it, is beyond the capability of any human.
Conversely, gaining insight into the impact of that data on our lives was previously beyond the capability of any machine. Sure, you could run figures through a computer and learn probabilities and statistics, but machines lacked the ability of humans to detect and apply nuance. Technologies like data mining and machine learning are finally gaining that ability by utilizing Artificial Intelligence (AI) for better resource management on all levels.
The Importance of Data Science in Business
Based on current trends, AI software will become the single most important technology for determining how companies make decisions and manage resources, both human and financial. Machine learning is a component of AI that performs data analysis to automate analytic model building. One of its strongest features is its ability to detect patterns in data and spot inconsistencies in these patterns to help us draw conclusions or make decisions.
In addition to altering how companies conduct business internally, data science will change the way businesses brand themselves and compete. Internet marketers are using AI-generated algorithms to read data and detect insights without being pre-programmed to search for it in a specific location. This information is used to intuitively target content to users based on their history and preferences, even when these preferences aren’t stated explicitly. Anyone who uses social media will notice that ads appear on platforms like Facebook according to their likes and shares as well as their web browsing or search histories. YouTube routinely recommends videos and generates playlists based on viewing history.
Data science combines algorithms. predictive modeling, advanced statistics, and computer programming to teach bots to read data and make instantaneous decisions. The key distinction with AI is that the machine is learning without human direction, intervention, or input. This allows machines to perform routine, tedious, or time-consuming tasks independently, freeing time for humans to focus productivity and creativity on more important pursuits.
Machine Learning and Data Analysis
The favorable economic impact of big data analysis is expected to reach $33 trillion annually across all industries within the next few years. In publishing, AI will produce up to 20% of all content put out by businesses by the end of the year. That impact will be felt throughout the decision-making process, hiring and training protocols, and efficiency by saving about 95% more time through automated platforms. As they say in business, time is money.
Finance and Data Mining
One example of the value data mining has in business is the financial sector. Financial services companies use machine learning technology to gain insights into transaction and customer data for fraud detection. Analyzing the high volume of information generated, and using that analysis to detect trends and make adjustments in fraud prevention protocols, would take hours of manpower without automation. This tech also takes human error out of the equation to improve accuracy.
Another area where financial services put machine learning to use is customer retention. Known in the finance sector as ‘customer churn,’ banks and other institutions can use AI to learn why customers stopped doing business with them. Retaining current customers is more lucrative – and far less expensive – than devising marketing campaigns to acquire new ones to replace them. Companies like NGDATA discovered the solution to customer churn through data analysis with the aid of big data technologies.
Healthcare and Data Mining
Much like the real world medical industry, healthcare technology is one of the fastest growing sectors. It benefits from data science in a number of ways, and its future potential will improve healthcare delivery and outcomes. Everyday fitness and preventative care are streamlined through apps like Fitbit, and sensors on wearable devices can monitor patient’s health 24/7.
Having health information collected, transmitted, and analyzed in real time improves diagnostic accuracy and speed as well as the effectiveness of treatment. Access to timely insights that are informed by accurate data and analysis allows doctors to innovate care and devise more effective treatment plans.
Fuel Industries and Data Mining
Big Oil isn’t just drilling for black gold these days; it’s also mining big data. Data-gathering sensors allow companies to save billions of dollars on everything from supply management to production. They’re also helping in the field by identifying safety hazards, avoiding outages, and using automation more effectively for drilling and extraction.
ConocoPhillips is one example of how data analysis is playing a big role in their company. Representatives state that the sensors its company has scattered over its oil fields cut the drilling time in half for their new wells in the South Texas Eagle Ford shale basin. The company was able to compare data from hundreds of sensors that are programmed to auto-adjust the speed of drilling and the weight on individual drill bits to accelerate extraction. This cut the extraction time considerably, according to the VP of strategy, exploration, and technology for the company.
A 2017 survey conducted by the firm of Ernst & Young gathered information from 75 gas and oil companies. They learned that 68% of these companies invested at least $100 each in data analytics technology over the previous two years. What’s more, 3/4 of the companies surveyed routinely allocate 6 – 10 percent of their budgets to digital technology investment alone. This trend is only expected to grow as more companies realize savings at the very level of production.
How Organizations Are Using Artificial Intelligence to Increase Revenue
One way businesses improve their bottom line is by accessing and implementing data in daily decision making. Data science technology overcomes problems companies face deriving meaning and value from data extraction and analysis by removing human error and fallibility. It does so by detecting data patterns and anomalies that trained analysts to miss, allowing business leaders to make more informed decisions based on insights derived from contract data.
Using the data-driven information to improve accessibility and analysis by even 10%, a large corporation will add up to $65 million in net revenue. Companies are also discovering the need for further investment in recruiting data scientists with the expertise to extract the data and use it effectively based on the resulting analysis. Once more businesses realize the ROI in developing data science in their own companies, this upward trend will continue.
Thousands of hours are spent each year just analyzing contracts. These manual reviews are not only time-consuming, they waste productivity and often provide inaccurate or outdated results. By the time a manual analysis is completed, relevant information may have changed, affecting the validity of data toward timely decision making. Using automation for contract data extraction and review improves the business intelligence gleaned from such data. This causes a positive, business-wide ripple effect across all areas of business function, including sales, procurement, human resources, and marketing.
Resource Management and Procurement
Areas like hiring, departmental evaluations, and inventory control are streamlined though AI. Human resources departments deploy such technology in evaluations and pre-employment investigation using some of the same technology that tells your social media platform your viewing preferences. AI can also perform more detailed and far-reaching analysis of previous posts and determine risk factors before hiring. Beware, social media junkies: more than 50% of companies check out their employee’s social media profiles.
Artificial Intelligence also streamlines the automatic processes. Currently, 30% of corporate leaders use voice recognition software to perform tasks previously done manually. This technology can prioritize email or return calls automatically based on importance. But, the value goes beyond the level of a virtual assistant to make a huge impact on productivity.
Marketers can turn over routine tasks like email campaigns and social media interaction to automated technology. Automated marketing using AI allows marketing departments to obtain important data, analyze the information, and prioritize actions based on the analysis. In turn, marketing professionals have more time to devote to the important business of increasing revenue as well as focusing on customer acquisition and retention.
The Future of Robotics and Automated Processes
AI, using data science and other technologies, is already changing industries as diverse as retail, eCommerce, and hospitality. As more corporate sectors discover the benefits of adopting AI technology, the value derived from these technologies will enhance their impact on society as a whole. This includes industries like healthcare and transportation as well as government organizations and the military.
A recent article in Forbes magazine states that within the next two years, 1.7 megabytes of new information will be created each second for every human being in existence. Going further into the future in 2025, the IDC predicts that 1 trillion networked devices will be interconnected. That’s a lot of information for businesses to sort through and convert to useful data, and AI-based technologies will be at the forefront.
Increased productivity through automated workplaces does not exclude people. As companies streamline core functioning, they’ll have more time and money to invest in their workforce. Studies show that more workers are concerned with a quality work experience, and are more invested in companies that help them reach their potential. When companies engage their employees, it creates stronger companies, improves loyalty, and reduced staff turnover. This, in turn, saves money on training and retention, reduces absenteeism, and further enhances productivity in a more focused way.
Ultimately, this filters down to the customers, who are the reason companies are in business. Within the next three years, 85% of customer service platforms will use AI to communicate with customers. In addition, satisfied workers mean better quality products and improved services, which leads to happier customers. This creates a sort of satisfaction feedback loop that will only be further strengthened through smart technology.
The rise of AI and concepts like the Internet of Things (IoT) will also offer advantages that improve the working environment and office design. Using data analysis, companies can introduce energy-saving technology that can adjust the lighting, temperature, and sound in offices and meeting rooms based on occupancy and purpose. This technology can even let employees know when the bathroom is occupied before they leave their desk.
Safer Transportation and Infrastructure
Safety and efficiency aren’t relegated to the office. Transportation will see an almost complete transformation over the next few years with advancements in smart roads and vehicles. Companies like Uber have been instrumental in evolving driving technology, making self-driving cars a reality. Preliminary testing shows that drivers save up to 50 minutes per day on their commute. This will also reduce traffic congestion and pollution.
Researchers at Northwestern’s McCormick School of Engineering are working on other ways to implement AI. They believe it can be used to monitor traffic and track congestion through intelligent surveillance. This can be achieved by replacing traffic cameras that use human monitoring with ones utilizing a machine learning platform. The technology can be placed at strategic points within the traffic grid, detect traffic patterns, and make predictions in real time. Traffic video surveillance that uses AI can perform quicker, more accurate evaluations to make meaningful recommendations for improvement.
While most public expenditures are invested in deploying sensors to increase efficiency and save money, government agencies and engineers are using AI and machine learning in other ways. Data mined through data science technology can be used to improve public safety, deliver utilities and public services more efficiently, and reduce response times during public emergencies. It’s not surprising that AI has also found a home in many military applications.
Nextgov predicts that machine learning and AI will evolve very soon to become incorporated into nearly all core platforms. This will give agencies more flexibility in areas like threat evaluations, risk management, and emergency response. Such efficiency will save time, money, and countless lives.
Artificial Intelligence and Security
Of course, whenever technology is involved, security is also a concern. There are some who fear to turn over any processes and decisions to machines, no matter how intelligent. Others express concerns about privacy and basing decisions that affect real people on the evaluations of a computer. However, no technology removes human oversight entirely, and the benefits of AI for security out-way any imagined risks to individuals.
Outside of limiting security risks in tech deployment, machine learning technology bolsters security in other areas. Artificial intelligence shows great promise toward preventing prevent identity theft. It can also identify and thwart hacks into government and corporate computer systems. The savings to government agencies, businesses, and individuals is nearly immeasurable. Since cybersecurity is an increasing global concern, you can be sure that focus on investment, research, and development in this area will continue in all sectors.
What’s Your AI Fear?
Some in the service and manufacturing industries fear technology will lead to massive job loss. Others fear that reliance on it will cause us to lose our humanity. However, technology should enhance human interaction and productivity, not replace it. Finding and maintaining that balance is the next challenge in AI.