You’ve undoubtedly heard about generative artificial intelligence (AI) at this point in one form or another. Whether it's the ChatGPT language model from OpenAI, AI-powered image generators, or even AI tools implemented into your workflows, the reality of artificial intelligence in business and general society is coming to fruition.
AI has captivated the scientific, technical, and entertainment industries for decades. However, realistic AI solutions are just recently starting to come onto the scene. With that in mind, it’s important to realize that these solutions are only scratching the surface of AI’s potential, and there are still a lot of unanswered questions regarding how to apply AI in business, how to responsibly implement AI solutions, and the ultimate direction of AI tech development.
On top of the questions surrounding practical implementation, there are also several vital legal aspects that need to be addressed when it comes to generative AI, especially in the realm of copyright law.
Successful adoption of AI is another challenge faced by business leaders, as many decision makers understand the potential of AI, but lack a practical roadmap for real implementation that actually delivers an ROI.
Hear from our very own experts on what we’ve learned implementing AI ourselves in Impact’s webinar, Lessons Learned from Incorporating AI into Business Processes.
Examples of Artificial Intelligence in Business
AI has moved from theory to practice, becoming an integral part of how organizations operate. Its applications range from improving customer interactions to optimizing complex processes. Here are some of the most common ways businesses use AI today:
- Customer Support: Chatbots and virtual assistants handle routine inquiries, provide quick responses, and reduce wait times.
- Data-Driven Decisions: Predictive analytics helps companies forecast demand, manage risk, and identify growth opportunities.
- Operational Efficiency: Automation powered by AI streamlines workflows in areas like supply chain management, logistics, and HR.
- Fraud and Security: Machine learning models detect suspicious activity and prevent fraud in real time.
These are just a few ways in which AI is being used across business functions today.
Customer Service and Communications
AI is transforming customer service from a reactive function into a proactive, data-driven experience. Businesses are using AI to automate routine tasks, personalize interactions, and improve communication across channels.
One of the most visible applications is the use of intelligent chatbots and virtual assistants. These tools handle common inquiries, process transactions, and provide instant responses, reducing wait times and allowing human agents to focus on more complex issues.
AI also enables personalization at scale. By analyzing customer data such as purchase history and browsing behavior, machine learning models can deliver tailored recommendations and responses, creating a more relevant and engaging experience without manual effort.
Natural Language Processing (NLP) adds another layer of sophistication by analyzing tone and context in messages or reviews. This allows businesses to gauge sentiment in real time, identify potential issues early, and respond appropriately. Similarly, AI-powered translation tools make multilingual support seamless, ensuring customers receive accurate assistance regardless of language or location.
Finally, predictive capabilities allow companies to anticipate customer needs before they arise. For example, AI can flag potential service disruptions or product issues, enabling proactive outreach that reduces frustration and builds trust.
Customer Experience Customization
Personalization has become a cornerstone of modern customer experience, and AI is the engine that makes it scalable and effective. By analyzing vast amounts of data in real time, AI enables businesses to deliver interactions that feel tailored to individual preferences without requiring manual effort.
AI-driven recommendation systems are one of the most common examples. These systems use purchase history, browsing behavior, and engagement patterns to suggest products or services that align with a customer’s interests. This not only improves satisfaction but also increases conversion rates.
Beyond recommendations, AI supports dynamic content personalization. Websites and apps can adjust layouts, messaging, and offers based on user behavior, creating a seamless experience that feels relevant from the first interaction. Similarly, AI-powered email marketing platforms craft individualized subject lines and send times to maximize engagement.
Adopting AI in Business
As AI continues to advance, the use cases will only continue to expand. From data analysis and customer experience optimization to more critical use cases, like churn prediction. AI has the potential to be an extremely powerful business tool that allows your employees to work smarter. However, seeing a true ROI from AI integrations requires a dedication to preparedness before onboarding.
By taking the time to set a foundation for successful AI onboarding, training employees, and pairing AI solutions to specific problems in your organization, you’ll find a much smoother path toward AI implementation that gives you the results you’re looking for.
One of the difficulties in finding the right balance of AI tools for any company is in the tool identification and selection process. There is a seemingly unlimited number of options when it comes to AI tools and solutions, and sifting through all that noise can be tiresome – leading to organizations onboarding tools without any real purpose or intention.
AI Today and a Look at AI Tomorrow
Organizations currently use AI to automate repetitive tasks, analyze large volumes of data, and deliver personalized experiences at scale. These applications are practical and measurable, reducing costs, improving efficiency, and enabling faster decision-making.
Current AI technologies focus on areas such as natural language processing, predictive analytics, and machine learning models that learn from historical data. Businesses rely on these tools for customer service, fraud detection, supply chain optimization, and marketing personalization. In short, AI today is about making existing processes smarter and more efficient.
Looking ahead, the role of AI will expand from optimization to innovation. Emerging trends include generative AI for product design and content creation, autonomous systems for logistics and manufacturing, and advanced decision-support tools that combine AI with real-time data streams.
Sustainability will also become a key focus, with AI helping organizations reduce waste, optimize energy use, and meet environmental goals.
As these technologies mature, businesses will shift from using AI as a support tool to integrating it into core strategy. The future of AI is not just about doing things faster, it is about enabling entirely new ways of working and creating value.
Wrapping up on Artificial Intelligence in Business
AI is a white-hot topic right now, and it may feel like everyone is using artificial intelligence in their businesses. However, the adoption, implementation, and even exploration of the technology is a much slower turning wheel than it seems on the surface.
Cybersecurity, data privacy, legality, and cost are four of the major hurdles generative AI tools still need to clear. Perhaps the largest hurdle that AI still needs to surpass, though, is proving its value in the context of a major business case that yields strong data which other decision makers can then use as fuel to champion an AI initiative in their own organization.
Right now, there’s a lot of steam stemming from generative AI conversations, but there aren’t necessarily the flames to match.
Get even more information on adopting AI from Impact’s experts in the webinar, Lessons Learned from Incorporating AI into Business Processes.