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Artificial intelligence (AI) left the realm of science fiction long ago and has become an integral part of our everyday life. Businesses of all sizes and in different industries are using AI-driven technologies to facilitate various processes. Here's an overview of what AI is, the benefits of using AI technologies, AI applications in business and key considerations when implementing AI.

What is artificial intelligence?

The most common AI-driven technologies include machine learning (ML) and deep learning (DL). There are also sub-fields such as evolutionary computation, robotics, expert systems, natural language processing (NLP) and fuzzy logic. 

They enable computers, robots and machines to imitate the perception and decision-making capabilities of human cognition. We can train computers to solve problems through reasoning and learning, as well as interpret language, perform complex tasks, analyze data and make predictions.

Benefits of using AI in business

AI is a critical component in many digital transformation strategies. It can bring tremendous value to many business processes and operations. Here are the benefits of leveraging AI technologies in business:

  • Improve productivity: Robotic process automation (RPA) and business process automation (BPA) tools can handle tedious and repetitive tasks so companies can allocate human capital to strategic and high-value activities.
  • Reduce errors and delays: Many manual processes are time-consuming and error-prone. AI-driven automation technologies help minimize costly mistakes and eliminate bottlenecks to improve operational cost-efficiency.
  • Speed up business processes: AI can help shorten product development cycles and time-to-market, so companies can realize ROI for their development budgets more quickly while gaining the first-mover advantage to increase market shares.
  • Improve customer experience: AI-driven technologies, such as chatbots, can deliver personalized customer interactions 24/7 to resolve issues and provide support. Not only can this shorten the time to resolution but also reduce support costs.
  • Support accurate data-driven decision-making: AI-powered data analytics software can process vast amounts of data to generate timely insights that support decision-making in today's fast-paced business environment.
  • Facilitate compliance and governance: AI technologies can monitor business processes to catch issues instantaneously, recommend actions and initiate responses. These safeguards help companies ensure regulatory compliance and enforce data governance policies.

Applications of AI in business

AI-driven technologies can be found in many business applications, such as:

  • Customer interactions and support: Machine learning algorithms and NLP allow chatbots to respond to customer requests, while AI-driven predictive analytics make relevant product recommendations to improve the shopping experience.
  • Audience targeting and programmatic advertising: AI can analyze large amounts of data in real-time to help marketers deliver ads to the right people in the right place and at the right time, both online and offline, to drive conversions.
  • Supply chain management: Machine learning algorithms can forecast demands to avoid overstocking or running out of in-demand products. AI can also facilitate logistics to optimize transit time and minimize costs.
  • Cybersecurity measures and data protection: AI technologies can scan and monitor the entire IT network, detect anomalies and initiate remedial actions to catch hacking activities, unauthorized access or malware attacks promptly to minimize damages.
  • Manufacturing: Endpoint devices (e.g., cameras, thermometers, motion detectors) can detect problematic behaviors, dangerous conditions or failing equipment to improve safety while optimizing equipment maintenance to minimize costly downtime.

Key considerations when implementing AI in business

Implementing AI-driven technologies isn't without its hurdles. For example, AI processes require access to vast computing powers. You'll also need to supply a lot of data, build models and invest in teaching machine learning algorithms how to interpret the information. 

As a relatively new field, there are fewer documented processes and standardized methods for AI implementation. Many data scientists and programmers have to build a practice from the ground up in their companies and overcome both technological and organizational challenges.

You must also ensure data integrity and develop trust in data throughout the organization, so stakeholders will utilize insights derived from AI-powered technologies to inform decisions.

Meanwhile, using AI technologies will require businesses to collect, process and store large amounts of data. Companies must implement well-designed data protection and governance policies to ensure the safety of sensitive information and compliance with various data privacy laws.

Working with a knowledgeable partner that has extensive experience applying AI to various businesses and industries can help you shorten the learning curve and optimize your resources. Get in touch to see more on what artificial intelligence is and how WWT can help you maximize your investment in AI technologies.