Recent innovations in AI is improving efficiency and performance in businesses operations. Research and Markets report that the AI market is projected to grow at a CAGR (Compound Annual Growth Rate) of 52% till 2025. AI will help entrepreneurs make more informed business related decisions. AI has the power to increase productivity of a business by integrating with information and communication systems thus delivering intelligent machine automation operations. This will be accomplished by providing early warnings of potential problems and broad based metrics.
Here are few ways how business owners can raise sales and productivity using Artificial Intelligence (AI) and Machine Learning (ML).
Previously, the approach to asset (equipment’s /appliances) maintenance was tedious and reactive. However, today with Artificial Intelligence and Machine Learning in place, organizations have started investing in predictive maintenance solutions that improves operating efficiency. Predictive maintenance uses sensors to track the conditions of equipment and analyses data on an ongoing basis, enabling organizations to service equipment when they actually need it instead of at scheduled service times, thereby minimizing downtime.
Machines can even be set up to assess self-conditions, order required replacement parts and schedule a technician when needed. Taking predictive maintenance even further, algorithms based on big data can be utilized to predict future failures. Thus, it can be said that AI-enhanced predictive maintenance of industrial instruments/machines can reduce annual maintenance costs, downtime and inspection costs. As per an A. T. Kearney survey in Industry Week of 558 companies using predictive maintenance, an average of 20.1% reduction in equipment downtime was thus observed.
Accurate Demand Forecasting
In GSC (Global Supply Chains) the demand forecasting is a fundamental tool for order planning and general strategy. GSC aids inventory supervisors in planning monthly orders, understanding seasonal trends, saving time on reordering and diminishing Stock-Outs & forecasting future broad based metrics. AI Technology learns from historical analytical data and can evaluate the complex factors involved in demand forecasting like market and economic forces, latest trends, etc.
AI enhances forecast accuracy and eliminates tedious algorithms associated with archaic programs. AI enabled forecasting ensures product availability, at the same time reducing inventory pile-up. It helps businesses understand their respective customer purchasing pattern in great detail. Using this market-basket analysis, sales teams are also able to create demand for other products.
AI can also improve demand forecast, it can also help the organizations generate new business. It is similar to consumer e-commerce websites, such as Amazon recommending products based on browsing or buying patterns. Recently, a retailer of bikes and kayaks with 600 stores reduced their inventory requirements by 7% and inventory carrying cost by 4.5% using AI enabled demand forecasting tools.
AI can also increase efficiencies of tasks as simple as taking physical inventory. A task that may take days to complete can be completed in only 24 hours using camera enabled drones that are deployed throughout the organization, scan items and check for deficiencies. Thus, using AI and ML systems can test multiple mathematical models of demand, production, outcomes with impeccable precision and also place material procurement orders based on this analysis.
Fig 1: Ways in which AI enhances productivity
Modern day consumers prefer customized, personalized, and unique products/services over standardized ones. Research & Developments in AI and software intelligence are enabling businesses to take personalized metrics to the next level by building services and products that are valuable to individual consumer’s needs.
Businesses have the opportunity to create differentiated propositions that may command a price premium, improve consumer traffic and conversion. A recent consumer survey by Deloitte showed that 20% of consumers are willing to pay a 20% premium for personalized products or services. Personalized product metrics enable brands to build greater trust with their customers via personalized offerings. 83% of consumers in both the U.S. and U.K. rely on trusted retailers using their personal information in order to receive tailored products, offers and recommendations.
Machines powered by Artificial Intelligence i.e., Machine Neural Networks using AI engines running Machine Learning Algorithms are capable of improving manufacturing processes and efficiency. AI system monitors parameters like cycle time, temperatures, quantities used, load balancing, Cache cycles, lead time, down time all to optimize the proficiency of business.
Machine Learning & Cyber Security
Analyzing sales calls is one of the crucial elements of business. In the past it was a manual process, now AI conversational tools are automating the entire process, thus reducing efforts and saving time. Such tools record each outbound call and pick-up cues that identify how the call went. Machine Learning (ML) is also an extremely accurate tool in combating Cyber Threats by spotting anomalies and discrepancies in day-to-day operations. Cyber Security using ML algorithms operate by monitoring data and it’s respective devices as is traverses it’s neural network. It also can send real time poll alerts throughout it’s network and can search for anomalies and compile those reports for present and future metrics to combat cyber threats.
Thus, machine neural networks can understand large volumes of data in seconds, providing perfect solutions second to none. With all this said Machine Learning with AI bases solutions enhances decision making, boosts efficiency and increases business sales. ML with AI solutions is rapidly changing business environments into the future and beyond.