Artificial intelligence in business helps to automate tasks, analyze vast amounts of data, generate valuable insights, and make more intelligent decisions. However, besides its numerous benefits, AI applications raise essential concerns in data privacy, ethics, dependence, and security. It makes business owners doubt the practicality and safety of AI use in the workplace.
In this guide, Uvik, an IT staff augmentation company, examines significant pros and cons of AI in business. We review case studies of AI in business to highlight how well-known companies leverage this technology, mitigating the risks of its applications in the workplace. Finally, we spot some future trends in the uses of AI in business.
Pros of AI in Business
According to the most recent research, 35% of companies globally use AI in their operations. More than 50% plan to implement artificial intelligence for business by the end of 2023. Let’s look at the benefits of AI in business, driving the adoption of this technology in the corporate world.
Efficiency and Automation
Adopting AI for business results in higher efficiency, streamlined operations, and improved client experiences. A recent Accenture study found that artificial intelligence can boost productivity by at least 40%. Furthermore, AI-enabled data collection, automation, decision-making, and cybersecurity can increase profitability by 38%.
AI-enabled software bots allow companies to create automated processes for manual, repetitive, and rule-based workflows. AI automation improves process effectiveness, increases customer satisfaction, and boosts labor productivity. It also reduces costs and risks, promotes product and service innovation, adds value, and successfully monitors and identifies fraud.
Data Analysis and Insights
AI technologies significantly impact data analysis, providing new capabilities to extract valuable information from vast amounts of data. Adopting AI allows businesses to enhance decision-making using more efficient, economical, and precise marketing strategies. By using AI in marketing, companies can increase audience engagement and build a solid online brand.
AI-driven predictive analytics is an application of artificial intelligence in business that helps to spot future trends. It enables enterprises to optimize stocks, improve delivery times, increase sales, and eventually reduce operational costs. Integrating predictive analytics insights with AI makes future forecasting more precise and timely. Companies that don’t use AI-driven predictive analytics risk falling behind.
Improved Customer Experience
Companies that excel at personalization generate 40% more revenue than those that don’t. AI-powered personalization entails gathering and analyzing massive volumes of client data, ranging from browsing and shopping history to social media interactions and demographic data. This data is used to identify each customer’s unique preferences to offer recommendations.
AI-powered chatbots and virtual assistants use machine learning algorithms and natural language processing (NLP) to interpret consumer requests. They respond faster and more consistently than human workers. Intelligent systems used in AI chatbots provide tailored services and recommendations based on the customer’s preferences, history, and context.
According to Harvard Business Review, companies who use AI to sharpen predictions, enhance efficiency, and optimize real-time pricing or stock control of their products have a competitive advantage over those still cautious about utilizing AI for these goals. As AI technologies expand, they become increasingly important for maintaining a competitive edge.
AI drives innovation with its ability to analyze massive volumes of data, learn from patterns, and make autonomous decisions. This technology helps improve the functionality of existing products and enables the creation of new AI tools for business. Moreover, product managers can use algorithms to brainstorm new product features, designs, and solutions efficiently.
Enhanced Risk Management
With AI technologies, companies can automate risk identification, assessment, and management. AI and machine learning algorithms process enormous volumes of data in real time, discover patterns, and anticipate data-based outcomes. It enables companies to
detect and respond to potential threats and vulnerabilities promptly and effectively.
AI can reduce financial risks by evaluating and predicting market fluctuations. AI techniques make incorporating external data sources into financial forecasting models easier. Organizations can get deeper insights into various financial performance factors by integrating data from sources such as social media, economic indicators, industry trends, or customer opinion.
Scalability and 24/7 Operations
Delivering outstanding customer experiences is critical to scaling successfully. AI-powered technologies have the potential to make a difference, adapting to high workloads and scaling as needed. Chatbots, interactive agents, and voice and mobile assistants are AI systems that enable a smoother customer experience.
The 24/7 availability of AI-driven customer support and services ensures businesses can operate efficiently across different time zones. This accessibility helps streamline issue resolution to meet clients’ demands. Automated customer support and order processing allow companies to capture leads and conversions at any time of day and improve cost-effectiveness.
Cons of AI in Business
While the list of AI benefits for businesses is impressive, some concerns and risks are associated with applying this technology in the workplace. Let’s look closer at some of them.
Data Privacy and Security
Artificial intelligence is vulnerable to cyberattacks and data breaches. As AI systems become increasingly integrated into business infrastructures, they can become significant targets for cybercriminals. Data breaches can have severe implications, such as identity theft, fraud, or other invasions of privacy.
Ethical use of AI and data requires considering what data should and should not be linked with other data and how to store, move, and use it safely. Privacy, bias, access, personally identifiable information, encryption, legal requirements, and constraints are all considerations of AI’s ethical use.
Dependence and Reliability
As you implement AI into your work process, you become dependent on it and design your operations around it. In this case, dealing with the consequences of AI system failure will be challenging. Overreliance on AI decision-making can result in the acceptance of inaccurate AI results. It can lead to errors and issues, causing reputational losses and missed revenue opportunities.
Initial Implementation Costs
To be fully effective, AI technology should be custom-built. It also requires the most recent hardware and software to keep updated and meet the evolving standards. It involves high upfront expenses. Despite the high ROI, not all businesses can make such an investment. Small companies may struggle to acquire finances to implement AI into the work process.
Case Studies of AI in Business
In this section, we examine how established organizations benefit from AI technology, implementing it to improve various business functions across multiple industries. Let’s look at successful case studies to understand the role of artificial intelligence in business.
Customer Service and Support
The world’s leading tech giants, like IBM and Microsoft, use AI-powered chatbots capable of human-like communication. Chatbots powered by IBM Watsonx Assistant provide quick and precise responses and perform complex transactions. It’s made possible by employing robotic process automation and backend interfaces with business processes. Microsoft Power Pages allows the addition of AI-powered chatbots to deliver efficient customer support for website visitors.
Amazon Alexa for Business helps organizations streamline task execution, improve productivity, and enhance accessibility through voice-activated AI. Alexa for Business assists with meeting scheduling, setting reminders, and procuring supplies. Employees can use voice commands to make phone calls and join virtual meetings without touching hardware.
Sales and Marketing
Companies like Salesforce leverage AI to predict customer behavior and optimize sales strategy. With AI integrated into Salesforce, every connection with a customer is tailored to their requirements and preferences. AI technologies evaluate client behavior patterns, predict their needs, and create tailored experiences by harnessing massive volumes of data.
Netflix and Spotify use AI to recommend content and playlists to users based on their viewing or listening history. Netflix’s algorithm learns on its own and continues to collect data. Logging more Netflix hours improves the quality of Netflix recommendations. Like Netflix, Spotify leverages user data, from playlist creation and listening history to interaction with the platform, to forecast what they may want to listen to next.
Supply Chain and Logistics
Walmart utilizes AI to optimize inventory management by predicting product demand to reduce overstocking and stockouts. The company has deployed specialized scrubbers equipped with inventory scan towers that can differentiate between brands and their inventory placements on the shelves with more than 95% accuracy. The technology considers the shelf depth, making it easier for employees to refill products.
Delivery companies employ AI to optimize delivery routes, minimizing fuel consumption and delivery times. UPS uses AI-enabled predictive system data analytics called Orion. Customers receive the most accurate tracking data as a shipment is routed through the system from start to finish. Drivers are provided with the best routes to stay within delivery windows. It increased processing power with tens of thousands of route improvements occurring in real time.
Finance and Banking
Banks such as JPMorgan Chase employ AI to identify fraudulent transactions and protect customers from financial losses. The bank uses advanced AI and machine learning to detect real-time fraudulent activity. Their system examines transaction data, user behavior, and spending trends. It helps to spot potential fraud and business email compromise and trigger alerts.
Companies like Wealthfront and Betterment offer AI-driven investment advice and portfolio management. These robo-advisory platforms use AI algorithms to deliver personalized investment advice to individual clients at a lesser cost than traditional financial advisors by evaluating vast volumes of data on market movements, risk tolerance, and investment goals.
Companies like IBM Watson Health (now Merative) assist doctors in diagnosing diseases by analyzing patient data and medical literature. The company is developing an AI system to help physicians diagnose and treat cancer tumors more quickly and effectively. It allowed us to incorporate various data sources to generate valuable insights and clinical advice.
Pharmaceutical companies like AstraZeneca use AI to accelerate drug discovery by analyzing massive datasets. In collaboration with BenevolentAI, AstraZeneca uses AI and machine learning to discover and develop new treatments for chronic kidney disease (CKD) and idiopathic pulmonary fibrosis (IPF). Machine learning allows systematic data analysis to identify relationships between facts, while AI-based reasoning helps to discover unknown connections.
Foxconn, a renowned electronics company, uses AI-based computer vision systems to inspect and identify defects in manufacturing processes. The company has implemented AI-powered visual inspection technologies on its manufacturing lines. They use machine learning techniques to detect flaws in electronic components such as circuit boards. Foxconn reduced faults by 95% and enhanced production efficiency by automating the inspection process.
General Electric employs AI to predict equipment failures and optimize maintenance schedules. The company has implemented generative AI to evaluate sensor data from manufacturing lines and discover patterns that lead to machine failures. It helps them avoid unplanned downtime and maintain consistent production levels by spotting anomalies early.
Online retailers like Amazon use AI to adjust prices in real time based on customer behavior, demand, competitor pricing, and weather. Amazon sellers can easily maintain competitive prices using dynamic pricing. If other Amazon sellers lower their prices, AI-powered dynamic pricing responds quickly to maintain competitiveness.
Zara, a leading fashion retailer, uses AI to manage inventory, ensuring popular items are always in stock. The company employs computer vision technologies to check real-time inventory levels in its stores and warehouses. The AI-powered cameras track product movement, allowing the company to refill inventory and quickly keep popular items in stock.
Energy and Utilities
Utility companies like PG&E use AI to optimize real-time electricity distribution, reducing outages and improving efficiency. The company develops deep learning applications to achieve maximum grid reliability and integrate distributed energy resources, enabling more human-like and independent decision-making. It allows PG&E to prevent loss of electricity and helps them restore electricity to their customers more efficiently.
Companies like Google-owned Nest offer AI-driven smart thermostats to optimize home energy usage. Nest thermostats allow keeping the perfect temperature while saving energy and cutting monthly bills. They use AI sensors and connected devices to assess the presence of people in the house and prevent heating or cooling an empty building by turning on energy-saving mode.
What is the Future of AI in Business?
- AI will continue to automate tasks, leading to job displacement for some workers. Over the next five years, artificial intelligence in business will disrupt over 300 million jobs worldwide, automating routine and non-routine prediction tasks and decision-making.
- AI will also create new jobs and opportunities, especially in developing, maintaining, and using AI systems. In some occupations, augmentation due to AI will lead to increased employment in fields like industrial engineering and analytics. AI will also create new job titles such as digital assistant engineer, warehouse robot engineer, and social media content tagger.
- AI will be used to develop new products and services, creating new markets and opportunities for businesses. Scientific research endeavors will revolutionize artificial intelligence, accelerating data analysis and recognizing patterns. It will stimulate breakthroughs in various industries and open new revenue streams for businesses.
- AI will be used to improve decision-making, helping businesses to be more efficient and profitable. AI technologies will provide businesses with new analytical capabilities, allowing them to extract valuable information from vast amounts of data. Companies will adopt AI to rely on more efficient and profitable business strategies.
The Bottom Line
Implementing AI for businesses offers numerous benefits by automating routine tasks, increasing efficiency, analyzing vast amounts of data, providing valuable insights, and enhancing customer experience. We reviewed AI in business examples to see how innovative AI solutions allow companies to gain competitive advantage, scale with 24/7 operations, and mitigate risks with automated threat identification, assessment, and management.
If you need professional help to implement modern business AI solutions, Uvik will assist you in leveraging these technologies while mitigating associated risks. Check our case studies to see how we help our clients accelerate software development. Our staffing company will help you locate and hire AI developers with proven expertise in just a week. Dedicated AI experts will develop a custom AI solution that matches your company’s specific demands and budget.
Contact us to get professional AI development consulting.