The first steps towards incorporating AI in business include defining what type of AI product you want to offer your customers or clients, identifying a specific use case, and laying out the expected behavior of that product as well as how it should be marketed and packaged so that customers are willing to buy it.
Artificial intelligence has reached a level of maturity that makes it suitable for commercial use. It’s now time for companies and their C-suite executives to look opportunistically at how AI can be incorporated into their business processes—and possibly even more importantly, why they should do so. When deciding whether or not AI is right for your company, think about its role: What are the low-hanging fruits for your specific niche? How will it affect customer experience? What will it add to a traditionally tedious business process? Is there an immediate need that can be addressed by AI?
Because each business is different, there are no straightforward answers here; what works for one might not work as well for another. But if you’re able to address these questions, you may find AI isn’t just the next big thing, but rather something that could make a significant impact on your top line. Here are some helpful hints and top use cases of artificial intelligence in businesses to help incorporate AI across the business functions in the most effective way possible.
There are two general types of AI products and services: one that companies can use internally to automate tasks (automation); and another that companies can use externally to serve their customers (personalization).
Automation is an overarching term for many specific tasks that AI technology can perform including anomaly detection, process optimization, sentiment analysis, image recognition, price prediction, voice recognition, and inventory management. The technology might sound familiar as each of these is a software program used by humans today in one or the other form of data analysis for automating business processes. However, what’s new is how quickly it runs its workflows and how well it performs them. While the legacy business and operational processes might take hours or days to complete a task; artificial intelligence can do it in seconds or minutes.
Similarly, personalization is an overarching term for many AI-powered features such as chatbots, virtual assistants, customer segmentation systems, and predictive analytics. These features help businesses understand and communicate with their customers better than ever before. Some of these features will also be automated over time but not all. Personalized AI-powered sales bots will still need human interaction to close deals and provide customer support when needed.
Artificial Intelligence Platforms
While most companies fall into one of the aforementioned categories, some focus on creating tools that make other AI applications more powerful or easier to build. These tools include algorithms that enhance existing data sets with additional information (e.g., medical datasets augmented with patient symptoms), processing capabilities (e.g., GPU-based computing), and improved accuracy rates via pre-trained models called transfer learning, etc.
Now that we have covered the fundamentals, let’s look at some artificial intelligence application cases in various key business domains.
Artificial intelligence in business has begun to revolutionize customer service—and it’s going to have a profound impact on how customers interact with businesses of all kinds. From text-based chatbots and auto-replying email messages that answer commonly asked questions to virtual assistants based on natural language processing that can field more complex requests (such as Tell me about your product roadmap), many companies are already implementing AI for customer service.
The possibilities are endless when it comes to AI technologies disrupting customer service. Right now, most executives see them as simply a cheaper alternative for businesses to leverage than human resources, but we’re already starting to see how AI adoption is changing the experiences and expectations of customers at every level.
AI systems are being used to disrupt marketing and help companies leverage customer data. Today, some of the most popular AI technologies—including machine learning, deep learning, natural language processing, computer vision, and expert systems—are being leveraged by top marketers and businesses around the world.
From self-service bots that improve engagement with customers, to recommendation engines that boost sales and lead generation software like augmented emails that get prospects on sales calls; these are just a few ways AI tools are disrupting marketing today. These tools can provide valuable insights into customer behavior and intent, allowing for more personalized marketing that boosts response rates.
Finance and accounting
Companies are realizing that AI can be used for anything from inventory management to invoicing and payroll. And thanks to a growing pool of AI startups, businesses have plenty of products and services they can choose from. The trick is finding which applications are best suited for your company. As you research products and services, think about how they might fit into your business model.
Think about which areas of finance and accounting they could disrupt and brainstorm ways they could help improve your customer experience. Does your accounting software have any trouble with double-entry bookkeeping? An AI program might be able to find errors faster than a human accountant, saving you time and money down the line.
Impact of AI on Sales
Sales organizations, as well as salespeople, need to be proactive about adopting AI and leveraging it for their advantage. The ability of AI-powered tools to automate decision-making processes is particularly beneficial for teams that need quick and accurate information. For example, an AI-powered CRM can make decisions about what leads will require to follow up based on patterns observed from previous engagements with prospects. By automating lead management, AI frees up your sales team from mundane tasks so they can focus on engaging with customers at key moments.
Sales professionals might also use AI-powered systems in combination with analytics to optimize performance by tracking where deals fall apart or which steps take too long—and then train their staff accordingly. AI has already made a huge impact on B2B sales and there’s plenty more room for AI to grow. It’s important that businesses are prepared to capitalize on AI’s potential benefits now before competitors beat them to it.
AI technologies are disrupting HR operations by automating tasks such as employee recruitment, performance review, and training. Recruitment can be improved through artificial intelligence. AI is used to filter resumes and evaluate candidates before even getting a human involved. Several companies are now using AI chatbots based on natural language processing for initial screenings.
In some cases, AI bots are being taught how to conduct interviews on their own based on past conversations they’ve had with interviewers and candidates. Once recruiters find a candidate they want to reach out to, they usually check that person’s social media accounts or search history using machine learning algorithms; humans rarely read resumes all the way through anymore because of their formatting complexity.
Fraud detection and cyber security
AI is already disrupting fraud detection and cyber security. AI and machine learning are used to help flag anomalies and predict behaviors that may indicate a problem. For example, AI can identify subtle patterns of words and phrases to find emails with fraudulent offers or fake job opportunities before they reach customers. The same goes for cyber security; AI can be used to scan internet activity looking for signs of malicious software or abnormal behavior that could lead cybercriminals to attack company data.
AI can help businesses analyze data, make smarter decisions, and improve efficiency. Integrating AI into your business can help you create innovative products and increase revenue streams. However, AI technology isn’t always black-and-white – Read: AI challenges; it has many nuances and grey areas that must be considered when creating an AI product. Before launching an AI product into production, at least consider these factors carefully:
- Audience (who commissioned your product – or in other words who will use your product?)
- Problem (what data do you need to feed into your system?)
- Maintenance (how will you keep AI models fresh?)
- Definition of success (how will you measure progress?).
In this article, we shared a few tips to incorporate artificial intelligence in business and a range of AI applications across various organizational functions – Read: Cross-sector AI use cases. In case you want to learn more, feel free to reach out to our experts.