Investments in AI are growing at unprecedented levels as organizations use this technology to generate value. These significant investments support the importance and value this emerging technology and capabilities can bring to an organization. Further, the ongoing pandemic crisis and associated labor shortages have accentuated the need for AI adoption and automation across industries to capture efficiency gains, increase productivity or improve revenue generation from the constrained resource pools.
While some companies capture AI value at an enterprise level, others generate new revenue streams or reduce production costs at a departmental or functional level. This activity highlighted in a recent study conducted by McKinsey on the global state of AI in 2020 demonstrates how organizations have empowered their operations through AI. Utilizing artificial intelligence-powered apps to leverage their finance, marketing, supply chain, production, and sales operations, companies have improved their bottom line and created strategic advantage from improved insights and a shortened time to action.
Recognizing AI opportunities
Many companies are yet to realize the full potential of AI due to organizational and cultural barriers as highlighted by this recent McKinsey report. However, once the potential benefit is recognized, the strategic direction typically becomes an easy sell to top management for these largely untapped, high-value opportunities. Further, support is often gained throughout the organization with a top-down forward-looking business ROI analysis that anchors the effort in corporate strategic plans and decision making.
Identifying AI opportunities involves data and decisions. Data is not just the raw numbers sitting in databases or spreadsheets but also unstructured and alternative data gathered from non-traditional data sources that can precipitate previously undiscovered insights. Decisions are the answers to a few questions like what opportunities will arise from the current data to provide additional insights, where are the most important, impactful, and frequent decisions by humans taken in the organization that can be optimized.
Andrew Ng, a thought leader on AI and founder of Landing AI, states about identifying
opportunity – “any task that usually takes you one second (or less) of thought to
do is probably a good candidate for automation.”
In manufacturing
AI can be applied across the manufacturing industry to deliver business benefits such as improving reliability, improving operational efficiency, improving quality control on the production line, and for reducing maintenance costs. Every misalignment, incomplete assembly, or defective part matters in the manufacturing industry. Thus, the success of the production line critically depends on the close monitoring of production quality, including identifying defects correctly and consistently. AI can transform manufacturing by empowering the sector to:
– Use robots to perform repetitive tasks
– Inspect equipment and enable predictive maintenance with machine learning
– Build digital twins
– Detect defects with deep learning
– Provide root cause analysis
– Adopt generative designs for smart manufacturing
– Powerup the cognitive supply chains involving functions like demand forecasting, transportation optimization, and logistics route optimization via machine learning
– Forecast energy consumption with machine learning
In energy and utility
Emerging AI applications in the energy and utility sectors efficiently transform how we forecast energy consumption and manage energy. Smart grids, smart meters, and better access to weather data present untapped opportunities employing advanced technology like machine learning and deep learning for operational optimization and improved customer experiences. AI can transform energy and utilities by:
– Forecasting energy loads with machine learning
– Optimizing power generation, ensuring better performance and lower emissions
– Improving and optimizing distribution processes with machine learning and enabling smart grids with greater control and flexibility
– Supporting demand management and improving energy management systems and overall energy efficiency
– Facilitating maintenance with machine learning combined with sensors and signal processing systems
In healthcare
AI is ready to support the healthcare industry with various tasks – from administrative workflow to patient and clinical documentation, as well as image analysis and patient monitoring. With large volumes of patient and clinical data to be harnessed, AI, machine learning, and computer vision prove promising to analyze this big data and extract valuable intelligence to assist healthcare providers in providing early diagnosis and better treatment. AI can transform healthcare through:
– Automated or assisted diagnosis and prescriptions for better patient care with chatbots
– Prescription audits to minimize prescription errors
– Accurate real-time patient prioritization and triage with prescriptive analytics
– Personalized care and medications reducing costs and increasing effectiveness
– AI-powered robot-assisted surgeries with collaborative robots
– Advanced medical imaging insights with computer vision and deep learning
– Drug discoveries with big data and machine learning
– Fraud detection mitigating the risk of false claims with machine learning
In retail
Understanding customers has become very crucial in an on-demand economy. Post-pandemic, physical stores are hampered with weak sales. To increase sales, retailers are focusing on competitive advantages by embracing AI to automate time-consuming tasks and increase operational efficiency. A few ways where retailers can use AI to provide more personalized customer experiences include:
– Price, promotion, and markdown optimization
– Product sizing and fit assistance
– Customer care chatbots
– Forecasting demand and supply
– Monitoring store activity with IoT
– Smart virtual store design
– Smart checkouts
– Contextualized and real-time pricing
– Personalization
– Sentiment analysis or social media monitoring
– Customer acquisition and retention
– Intelligent product lifecycle management
– Fraud and threat detection
– Mixed reality experiences
– Delivery automation
In financial services
The financial services industry, like any other industry, has become more competitive. Banks use AI as an analytical solution and serve customers better and handle internal functions efficiently. AI works as a remedy for many challenges that the BFSI industry faces to reduce and optimize the cost of operations, customer acquisition, and merchant acquisition through:
– Generating value from open banking
– Enhancing in-house services and features
– Optimizing outbound communication
– Reducing operational costs with AI and NLP
– Process optimizations by handling bulk volumes of data with high accuracy levels
– Efficient risk management with accurate predictions
– Algorithmic trading processes to automate trades
– Fraud detection
– Financial counseling from digital assistants
AI is reshaping the industry with innovative methods of data collection and large-scale automation that open up previously undiscovered strategic opportunities for enterprises creating great benefit and value for customers. While many organizations are catching on quickly, a significant opportunity remains to leverage the relatively untapped value of AI versus the magnitude of the opportunity.
If you would like to learn more about the value that AI would bring to your business, send us your query to intellect2@intellect2.ai. Intellect Data, Inc. is a software solutions company incorporating data science and artificial intelligence into modern digital products with Intellect2TM. IntellectDataTM develops and implements software, software components, and software as a service (SaaS) for enterprise, desktop, web, mobile, cloud, IoT, wearables, and AR/VR environments. Locate us on the web at www.intellect2.ai.