“A bot might not take your job, but it could be your new coworker,” reads the title of an article on VentureBeat, and rightly so. Modern businesses are driven by data, for they need to keep the consumers pleased, operational processes refined, outcomes more profitable, and the ROI high.
But data alone cannot work the magic. It has to be processed and used by leveraging the apt technology. This is where Artificial Intelligence (AI) takes over to play a critical part in driving Machine Learning (ML), Natural Language Processing (NLP), and a host of other allied technologies. AI takes over the part of analyzing large data amounts without error and leverages the analytics for better operational decisions.
Integrating AI into workflows and businesses across sectors focuses on increasing operational efficacy, going beyond merely increasing profit and revenue margins. In this article, let us understand
- What is AI decision-making?
- How is it useful for enterprises?
- Business use cases of AI decision-making
What is AI Decision-Making?
AI decision-making is the process of analyzing large datasets and employing data analytics to make the final call on any business or service operation. This involves predictions and decisions based on concrete data instead of any human instinct.
The word “large” indicates that there’s “too much” data for humans to handle and identify trends and patterns. That’s precisely why businesses employ AI-powered technologies that can sift through massive structured and unstructured datasets and identify business-relevant patterns.
An example of the same could be AI helping pinpoint the tumor and complementing the healthcare providers’ efforts in finding cancer early. The same also applies to scrutinizing the state of automobiles, industry-specific equipment, machine-related performance, and much more.
In essence, this data processing involves several steps, including data crunching, trend spotting, detecting anomalies, and making complex analyses. Making decisions this way makes AI compliant and adept at optimizing workflows across sectors.
How is AI Decision-Making Helpful?
Earlier, humans determined everything, from deciding customer choices to planning marketing strategies and designing new products to determining their final costs. In the process, human emotions, and cognitive biases often crept in. Needless to say, filtering out cognitive biases is a must when making critical business and operational decisions.
Favorably, AI has taken over this task of unbiased analysis. It trains itself using collected data and builds data models, which then categorize and predict events. The same models are good to use with live data materializing from real-time operations (touchpoints), letting businesses and service providers make informed decisions.
For instance, Amazon’s use of its consumer data to roll out personalized marketing initiatives testifies to how effective AI is as a tool for predicting and acting upon consumer behaviors.
To that end, let’s explore some concrete use cases where AI decision-making works wonders.
Benchmarking Business Operations
Businesses roll out an enormous amount of heterogeneous data emanating from employee output, financial transactions, payrolls, supply chains, analytics, etc. ML algorithms take over the task of analyzing them and giving out patterns that help in adhering to the benchmarks and unbiased rerouting of administrative and operating tasks. As such, both employees and executives are equipped with the capacity to remain proactive.
Streamlining Product Launch
When multifarious factors are in play, decision-making is sure to become complex. A product launch, for example, involves:
- Walking through the concept.
- Setting it on the production floor.
- Determining price and marketing strategies.
As a result, a business needs to make dozens of decisions that involve investigating, prioritizing, optimizing, and forecasting.
AI-powered technologies sift through mountains of relevant internal and external data sources to streamline these processes. The concerned individuals thereupon use the analytics results to make sense of every step involved until the product launch.
Re-imagining Healthcare Delivery
AI-powered image recognition works wonders for diagnostic assessment. Radiologists earlier relied on their memory and physical archives to dig out relevant scan reports to help compare present cases and make required decisions.
AI-trained algorithms can review thousands of scans quickly and detect signs of a particular disease — as elucidated above with the example of “tumor.” It lets doctors proceed with evidence-based treatment plans and advance healthcare delivery.
Advancing Automotive Manufacturing
The automotive industry is among the frontline manufacturing industries that are using AI to its full capabilities. Integration of the Internet of Things (IoT) and AI uses historical and live data to fuel a wide spectrum of decisions.
Right from autonomous vehicles making their way through busy streets to making forecasts for predictive maintenance of plant machinery, AI is making decisions everywhere. In fact, Gartner predicts that 40% of the infrastructure and operations teams will employ “AI-augmented automation” by 2023.
Enhancing Customer Experience
Customers expect to be treated well, preferably with hyper-customized communication. This opens avenues for suggesting products based on previous buying history and browsing patterns – a key area that eCommerce platforms dole out using AI.
Evaluating customer behavior and predicting buying trends and patterns are some other important areas where AI decision-making plays a key role. Other related technologies, like speech recognition systems, help in improving customer query experience.
Likewise, providing customers information on, let’s say, their shipment status and managing last-minute order changes reflect upon AI’s prowess in incident management.
The Bottom Line
AI decision-making is helping businesses make faster, more accurate, and consistent decisions. It’s also assisting companies in building better products, improving operational efficiency, and enhancing customer experiences.
At Heptagon, we use AI to solve real-world problems across several industries — banking, education, manufacturing, retail, insurance, etc., to name a few.
Reach out to us to learn more about how AI-powered technologies can help your organization grow.