There's a great deal of conversation around artificial intelligence (AI) as we find ourselves, once more, in a turning point in the information age. The massive amount of data produced by our devices, sensors, and the Internet of Things (IoT) continues to grow. Turning this data into actionable insights and reaching new levels of problem-solving will require intelligent problem-solving abilities. This is where AI can come in.
What is Artificial Intelligence?
When most people hear the term artificial intelligence, the first thing they usually think of is robots. But actually, AI refers to the simulation of human intelligence in machines that are programmed to think like humans. These machines then mimic and execute tasks. The goals of AI include mimicking human cognitive activity.
Machines have far superior computational abilities than humans. They can sort through enormous amounts of data and use it to make better decisions. So the general idea behind AI is to have machines do the heavy thinking for us.
The ideal characteristic of AI is its ability to rationalize and take actions that have the best chance of achieving a specific goal. AI can:
- Find patterns, trends, and associations
- Discover inefficiencies
- Learn and become better
- Execute plans
- Predict future outcomes based on historical trends
- Inform fact-based decision
AI is being used across different industries including finance and healthcare, and as it evolves, it will continue to expand into other industries to solve
real-world challenges.
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What is Machine Learning?
Machine learning is a type of AI that allows computer programs to adjust when exposed to new data, in effect, “learning” without being explicitly programmed. Machine learning is similar to data mining in which databases are examined by humans to produce new information and insight. However, machine learning provides an unbiased analysis of the data.
How Can Artificial Intelligence and Machine Learning Help Different Industries?
In every industry, there are a myriad of interconnecting inputs and variables. Analyzing this complex data to derive meaningful value is often overwhelming, inhibiting our ability to find adequate solutions in a timely manner. Unlocking these complex scenarios such as how humans are likely to behave and interact can create opportunities.
A lot of the major tech companies are already developing artificial intelligence solutions. This allows these companies to:
- Automate and improve complex analytical tasks
- Look at data in real-time, adjusting its behavior with minimal need for supervision
- Increase efficiency and accuracy
Artificial intelligence will eventually touch nearly every industry on the planet. Here are a few ways AI can help transform certain industries.
Retail
Few industries have seen as much disruption as retail. Today, customers expect quick delivery, personalized digital experiences, and instant gratification. Meeting these customer expectations requires immediate insights into consumer behavior and business-critical data. For retailers, this means managing an ever-growing number of data sources while processing point of sale (POS) information quickly and effectively.
The disruptive impact of artificial intelligence in retail is seen across the value chain and is emerging as a powerful tool for retail brands to gain a strategic advantage over their competition. As online shopping replaces more and more brick-and-mortar retail stores, AI in the
retail industry is gaining speed.
Cyber Security
One of the industry leaders in cyber security, Cylance, applies artificial intelligence to cybersecurity in a preventative and predictive way.
According to
Cylance CEO and President Stuart McClure, their AI prediction technology looks at millions of files and attacks to learn exactly what makes them up. By understanding this mathematical DNA, they can prevent and protect against future attacks.
“It looks like we’re predicting attacks, when really, we’ve just learned through AI machine learning what the DNA of these attacks is.”
Reducing Energy Costs
Companies in the energy sector can use artificial intelligence to sift through vast datasets to predict and adapt to certain scenarios. They can reduce operational costs and mitigate issues proactively in the following ways:
- Increase automation
- Optimize asset management
- Improve operational performance
- Identify efficiencies
- Decrease downtime
DeepMind, a technology company that was acquired by Google in 2014 uses machine learning to help solve every day problems such as reducing energy usage. By applying DeepMind’s machine learning to Google’s data centers, they’ve managed to
reduce the amount of energy they use for cooling by up to 40 percent.
The problem was the data was too complex for traditional formula-based engineering and human intuition. Each data center had a unique architecture and environment that required a custom-tuned model. A model for one system may not be applicable to another. Therefore, a general intelligence framework was needed to understand the data center’s interactions.
They used historical data collected from thousands of sensors within the data centre such as temperatures, power, pump speeds, set points, etc. and used it to train an ensemble of deep neural networks.
By applying machine learning to the problem, DeepMind researchers were able to significantly improve the system’s utility in only a few months.
Healthcare
From detecting early forms of cancer or disease to analyzing MRI scans — essentially anything that’s data driven — machine-learning technology can bring huge benefits to the healthcare industry.
By analyzing large amounts of medical data, AI can help clinicians give faster and more accurate treatment to their patients, and can learn from to make better decisions going forward.
For patients, an AI-driven healthcare system could alleviate some of the burdens on a system struggling to keep up with the ever-growing demand. Having this technology in your pocket could help you make better health decisions, diagnose disease and other health risks earlier, avoid expensive procedures, and help you live longer.
Consumer Goods and Services
Shifting consumer demands has upended the relationship between brands and consumers. To succeed,
the consumer packaged goods industry needs a deep understanding of new consumer journeys. Only then it is possible to deliver personalized experiences driven by data. It’s the data across all lines of business – from manufacturing to marketing to finance – that increase innovation, improve agility, and better understand customers.
AI encompasses anything from Google search to self-driving cars. Netflix uses AI to
give viewers what they want by collecting mind-boggling amounts of consumer data. They know which shows you watch, what time of day, when you pause, rewind, fast forward, or skip. Everything from sentiment to viewing habits, Netflix sees it all in real time.
With over 30 million subscribers worldwide, they look at big data to influence their decision on which original programming viewers are likely to respond favorably to. After running the numbers through their AI technology, they determined that people liked David Fincher movies, films featuring Kevin Spacey, and the British version of House of Cards. Based on that information, Netflix bought House of Cards.
Finance
AI technology is being used to look at financial models to achieve greater levels of trend analysis, predict future pricing patterns, identify new markets, and assess supply chain risks.
Deep Knowledge Ventures, a Hong Kong–based venture capital firm announced their program called VITAL will be the newest addition to its board of directors. VITAL uses large amounts of data to make investment recommendations.
Finnish tech company
Tieto also uses an AI to help them make data-driven business decisions.
Government and Environment
Governments have a heightened responsibility to serve as an authoritative source of truth for their citizens. Synthesizing and distilling inputs quickly can help inform governments to make better decisions on important social issues, economy, and the environment, all in real time. To achieve this, government
organizations need a portfolio with the tools to break down silos, optimize processes, and turn insight into action, so they can focus on the challenges of tomorrow.
By
placing sensors on everything from streetlights to mountains, and then applying AI to all that data, governments can:
- Build more liveable cities
- Reduce poverty
- Prevent crime and terrorist attacks
- Understand climate change
The military is another area that could use big data to gain insights into tumultuous conflicts before they happen. By using satellite photo interpretation capabilities, artificial intelligence programs could identify potential targets and threats.
By analyzing speech patterns in communications, artificial intelligence can look for certain words and phrases that may indicate terrorist activity and then respond quickly to diffuse the situation before it escalates.
Procurement
Spend analytics software has been helping procurement departments make the most of big data. But with the help of AI, the procurement industry could overcome some of its biggest challenges.
AI software could offer:
- Risk analysis of suppliers
- Compare prices of suppliers
- Manage supply chain risks
- Monitor exchange rates
- Find the best value without compromising quality
Assisting with and accelerating buying decisions could translate to big savings for a company.
What Does it All Mean?
Regardless of what industry you’re in, the potential for artificial intelligence is huge. Machine learning and rule-based analysis can benefit you greatly from finding new ways to reduce costs, create efficiency, and to optimize working environments.
With more and more aspects of our lives and work generating vast amounts of data, it is all but inevitable that AI will contextualize the data and extract meaningful insights so that companies can make better decisions and improve their bottom line. And it's becoming imperative that businesses turn to an analytics platform that has AI capabilities to:
- Discover key influencers of your KPIs such as revenue, churn, and productivity
- Explore interactive charts and graphs, automatically generated based on your query
- Create time series forecasts to predict future results based on historical data
SAP Analytics Cloud uses machine discovery to help reveal insights from your data. It delivers rich data visualizations with an intuitive user interface so that you can gain a contextual understanding and situational awareness of your operations is crucial for making intelligent decisions.
