AI in Business: How to Do It Right
People and businesses are adopting artificial intelligence at greater rates than ever before. In Q1 of 2023 alone, total generative AI funding surpassed the 2022 budget by 4x, reaching over $10B. From content creation and text generation to synthetic data and chip design, AI empowers businesses to innovate quickly, improve productivity, and drive significant business value.
However, it’s not enough to use artificial intelligence as a technical exercise: You need to use AI in the business to improve outcomes and empower your team strategically. In this blog, we’ll dive into the versatility of AI in the industry outside of content generation, offer examples of artificial intelligence use cases, and break down the ideal AI journey, ensuring you have the tools you need to thrive. Let’s get started.
The Versatility of AI in Business
For many organizations, the most utilized benefit of generative AI has been content generation, but what’s incredible about AI is that it offers business-wide benefits. Here are a few of the most significant pros of AI across an enterprise.
Improve Operational Efficiency: People can significantly improve their productivity with AI. Imagine the effects of an entire business streamlining its tasks with automation. AI can help your team become more operationally efficient while also becoming more efficient itself. For example, artificial intelligence can support analysis, brainstorming, and ideation when you feed it relevant information and create roles that speak to you in a way you best understand.
Increase Revenue: With data-driven insights, automation, and predictive analytics, AI can help organizations drive revenue. For example, AI can analyze vast customer data sets to identify patterns and preferences, allowing teams to personalize their offerings. Similarly, AI-powered assistants can provide 24/7 customer support and improve satisfaction. With these improved customer experiences, they can drive sales and continuously improve.
Generate Business Ideas: By leveraging AI’s capabilities to perform data analysis, pattern recognition, and predictive modeling, AI can inspire and generate new business ideas based on market research, customer insights, competitive analysis, and predicting emerging technologies.
When used effectively and continuously, AI can offer benefits that empower businesses to remain competitive in an ever-changing landscape.
Artificial Intelligence Use Cases
AI provides various use cases that can drive value, acting as a personal assistant to each of your employees. Gartner has released several use case prisms that break down use cases across industries and focuses. For example, according to the Gartner use case prism for customer service, 18 primary use cases of AI are feasible and provide business value specific to customer experience. The following are a few of the customer service use cases:
- Agent Workforce Scheduling
- Customer Emotion Detection
- Offer Personalization
- Customer Segmentation
- Intelligent Contact Routing
- Predicting Customer Lifetime Value
- Hyper Automation to Improve Fulfillment
Each industry has its areas that AI can improve—the key is to learn how to harness it best to drive the results you’re looking for.
The Ideal AI Journey for Businesses
AI can empower your team to identify strategic opportunities that grow your business well into the future. Work with your experts to understand each use case and how it applies to your business. Your data and AI maturity journey will go hand in hand with your insights maturity. The ideal AI process should have the five following traits and answer key questions:
- Descriptive: What happened?
- Diagnostic: Why did it happen?
- Predictive: When will it happen again?
- Prescriptive: What will we do when it happens again?
- Optimized: How can we drive continuous improvement?
Ensuring your process offers these insights will help you optimize the results of your AI use. Don’t forget to double-check the journey with your subject-matter experts to ensure all information is reliable.
AI Best Practices
Businesses using AI need to have a clear AI policy that keeps important values in mind. For example, companies must maintain data quality, bring human-like intelligence to AI algorithms, and be careful about unintentionally baking bias into data and models. Here are essential best practices to include in your processes:
- Treat implementing AI as more than a technical exercise. Quality data is the heart of your business and must be protected.
- Bring the human aspect of intelligence to AI algorithms by relying on experts with deep domain experience who can maintain efficiency and accuracy.
- Implement guidelines to prevent introducing bias to algorithms, data, and models unintentionally.
- Intervene in each learning algorithm to ensure actions are accurate and reliable and have not taken a wrong step.
- Continuously update algorithms—don’t treat them as a one-and-done task.
- Validate before spending time, money, and energy on a use case that AI can improve or solve.
The Right AI Tools for the Job
Choosing the right Generative AI tool is crucial for maximizing efficiency and effectiveness. These tools can automate mundane tasks, provide data-driven insights, and even contribute to creative endeavors like content generation. By aligning AI’s capabilities with specific job roles or industry requirements, you can unlock new avenues for innovation and productivity.
Ultimately, the right tool can be a game-changer, offering a competitive advantage and streamlining operations. The perfect tool today may not be the perfect tool tomorrow. It is essential to constantly look for improvements to tools, as we are still in the early days of this technology, and competitors are eager to differentiate themselves from the crowd. New capabilities are being introduced regularly, and it is a good idea to follow a few different companies that align with your business needs and security requirements to understand their roadmap and what’s next.
In addition to the big players like OpenAI, Microsoft, Google, and Meta, there are many Generative AI players. Here’s a quick sample list of Generative AI tools that align with specific industries:
- ChatGPT: An AI model developed by OpenAI used for customer service chatbots
- Microsoft Dynamics 365 AI: Provides AI solutions for customer service including virtual agents
- Generative Design in Autodesk: Uses machine learning to come up with design solutions
- IBM Watson: Used for predictive maintenance and quality control
- KAI (Kasisto): A conversational AI platform helping banks with customer interaction
- Personetics: Uses AI for personalized banking
- IBM Watson Care Manager: Assists care management teams in human services
- Ayasdi: An AI platform used in healthcare for clinical variation management
Power and Utilities
- GE’s Predix Platform: Used for asset performance management in power and utilities
- Bidgely: Uses AI for energy disaggregation to help utilities with demand-side management
- Grant.io: Helps nonprofits find grant opportunities
- Vocdoni: Uses blockchain and AI to provide secure and anonymous voting for nonprofits
Remember, the effectiveness of these tools may vary based on specific needs and preferences. Exploring and evaluating each tool based on your industry and job role requirements is recommended.
As you can see, AI can drive significant benefits when handled carefully and correctly. When used to generate value beyond content creation, the technology can reshape industries, drive revenue growth, and foster innovation. AI is not a fleeting trend—it’s a powerful force that can drive businesses forward in an increasingly data-driven world.