How To Use AI in Decision-Making: Benefits and Examples

The average workday is one decision after another. You might need to choose a new hire, decide on a color palette for a marketing campaign, and narrow down a list of clients to focus on for the month — all within an hour. 

What if you didn’t have to tackle those choices alone? Great news: You don’t. AI in decision-making is becoming more common in the workplace. These tools can analyze options, predict outcomes, and make recommendations based on relevant data sets to save you from decision fatigue.

Ready to make smarter choices? We’ll dive into how AI systems can streamline decision-making, the challenges to watch out for, and the best ways to implement tools effectively.

How AI helps in decision-making: An overview

Whether you’re strategizing a product launch or fine-tuning an email to an important customer, your choices can make or break success. Let’s look at six benefits of decision-making with AI tools:

1. Accelerate decision-making: AI algorithms process enormous data sets in seconds, providing actionable suggestions that would take human teams hours or days to create. This speed is a big competitive edge when dealing with sudden market changes or new customer demands. 
2. Refine risk evaluation: History repeats itself, but for AI, that’s a good thing. AI systems can help you analyze historical patterns and real-time inputs to help you analyze potential risks and take proactive measures. 
3. Provide data-driven insights: Use AI algorithms to deep dive into customer behavior, uncover market opportunities, or analyze areas for team improvement. Whatever it is, AI laser-focuses your team’s time and energy. 
4. Enhance predictive accuracy: AI-generated forecasts for sales, customer needs, and market shifts allow your business to stay lean and jump ahead of the curve. This gives your business a critical edge, helping you plan proactively and pivot strategically — no matter what’s waiting at the end of the tunnel. 
5. Boost worker productivity: While AI handles repetitive, time-consuming tasks, your team can focus on creative problem-solving and high-level decision-making. From data entry to generating reports, AI does the work for you, allowing team members to channel their skills into stronger collaboration and productivity. 
6. Personalize customer interactions: AI tools can gauge customer preferences and behaviors to execute tailored experiences at scale. Whether it’s optimizing email blasts, recommending products, or powering chatbots, AI builds a path toward more meaningful connections with your customers. 

4 examples of companies leveraging AI for decision-making

Ready to upgrade your toolset? Here are four examples of AI decision-making tools in action:

1. Otter.ai provides actionable insights

Managers and collaborative team schedules often revolve around meetings — sometimes too many to count. Even if you aren’t heading into back-to-back meet-ups, it can be hard to turn the flood of information into action. 

Otter.ai enhances workflows and productivity by transcribing key discussions and converting them into searchable notes, action item lists, and follow-up emails. Otter also syncs with CRM software, using AI to automate data collection and keep customer insights organized and accessible. You can also ask Otter AI Chat questions about one meeting or all of your meetings to generate more insights or specific content related to your conversations. When it comes to making important decisions, all your information is set up and ready for action. 

2. LinkedIn enhances hiring decisions 

Some job postings receive hundreds of replies, making it tough to sort through resumes and find the perfect fit. LinkedIn’s AI-powered recruiting system helps hiring managers cut through the pile of CVs to find the top candidates. This tool isn’t just reactive — hiring managers can proactively headhunt talent, automate the recruiting process, and connect with the best matches for their needs. 

3. Salesforce uncovers customer behavior

When it comes to engaging with customers, you have to learn to speak their language. And keeping up with new trends, preferences, and consumer habits is no small feat. Salesforce Einstein uses AI systems to analyze customer interactions, uncover current needs, and close the sale. Generative AI models like this one engage with customers and salespeople alike to solve problems quickly and efficiently. 

4. Google Ads personalizes marketing campaigns 

Quality products don’t sell themselves. Personalization is key to connecting with your target customer in a crowded marketplace. Google Ads uses AI-powered algorithms to analyze customer behavior, from browsing habits to search queries and purchasing history. Leveraging this data allows you to build and automate targeted ads that speak directly to customers, boosting engagement and conversion rates.

3 challenges of AI decision-making

How does AI make decisions? It congests massive data sets into patterns and predictions that guide your decision-making. While this can be a major driver of efficiency and innovation, handing the reins over to technology can sometimes create more problems than solutions. 

Let’s break down three pitfalls to help you use AI responsibly and effectively:

1. Ethics and bias: AI doesn’t differentiate between fair and unfair practices on its own, which can raise ethical concerns in its data analysis and decision-making process. For example, bias in training data can stimulate discriminatory hiring recommendations or customer targeting. Businesses should carefully analyze the data AI systems rely on to make sure it’s inclusive and free of biases that could lead to unfair outputs. 
2. Hard to interpret: Machine learning technology mimics the human neural network. And sometimes, understanding the way AI systems work can be as difficult as untangling the human brain. A lack of transparency about how or why AI spits out certain outputs can make it challenging to explain or justify data analysis and decisions, which can hinder trust with stakeholders and team members. 
3. Data quality: AI is only as good as the data it’s trained on. Beyond bias, AI can create poor recommendations when fed poor-quality or outdated information. Regular quality checks ensure consistent, trustworthy results. 

Is AI replacing humans in decision-making?

AI can improve human capabilities, not take over the workforce. It excels at tasks humans struggle with, like processing vast amounts of information and uncovering complex patterns. But it lacks human qualities that power good decision-making. No algorithm can match skills like empathy, intuition, and understanding context. 

Imagine AI tools as symbiotic. AI frees up resources for human decision-makers to focus on strategy, creativity, and high-level judgment rather than being caught up in the nitty-gritty of administrative tasks and complex workflows. For example, AI in marketing can identify the most promising customer segments, but it’s up to professional marketers to craft a brand message that resonates. 

Simply put, AI tools are most successful when they work alongside humans, leveraging what makes each decision-maker uniquely qualified to make smart choices. 

Elevate your decision-making process with Otter AI Chat

Good conversations power good decisions. With so many ideas bouncing around, it can be difficult to keep everyone aligned and on course. 

Forget about sifting through recordings or scrambling to recall who said what — instead, ask Otter AI Chat questions, get instant answers, and ensure no detail of your valuable team conversations goes missing. 

Make smarter decisions with Otter AI Chat today.