How to Harness the Power of AI Tools for Business Success

AI tools for business are some of the most important (and interesting) technologies for supporting modern commerce and workplaces. And rest assured they will play a crucial role in the future as well. 

A growing number of users across industries such as healthcare, finance, retail, and automotive are embracing the power of AI platforms to help analyze everything from statistics in marketing to inventory management and payroll. They’re also using this advanced technology to innovate new products, services, and customer experiences and help make their employees more efficient overall.

In this post, we’ll look at how companies are harnessing the power of AI tools for business success, including areas where the technology is commonly deployed today. We’ll also examine some best practices for adopting AI tools for business and some key benefits of implementing AI solutions.

First, let’s look at why many businesses are eager to work with or expand their use of AI.

AI Technology and Its Impact on Business

Many businesses are grappling with inflationary costs, labor shortages, and the pressure to become more efficient to maintain customer relationships and compete. Small businesses, especially, can benefit from AI’s ability to increase productivity by automating repetitive tasks, streamlining and optimizing operations, and handling large volumes of data for analysis to provide valuable business insights. 

AI platforms can be invaluable to content creators, sales teams, customer service functions, and other users by freeing up employees to handle more high-value tasks. AI tools can also reduce costs, drive revenue, and amplify return on investment. Some of the best AI tools in the marketplace today are readily accessible and cost-effective, even for small businesses.

The Top Applications of AI Tools in Business

So, where are businesses typically incorporating AI capabilities? Here are seven key areas where AI tools for business can create value for users by streamlining workflows:

1. Customer Relationship Management (CRM)

It’s a rare CRM system today that fails to offer some form of AI to automate customer service tasks and provide functions throughout the business with better, more organized customer data and tools. Examples of AI in the CRM arena include:

• Chatbots and virtual assistants — These tools provide self-service flexibility to users and remove simple requests from customer service agents’ workflows, freeing them up to focus on more complex problems that require a human touch.
• Sentiment analysis — There’s an array of tools to choose from that use machine learning to collect consumers’ brand mentions in various channels and analyze the sentiments behind them. These tools provide valuable information to customer service as well as sales and marketing.  
• Customer segmentation and targeting — AI technology can rapidly “slice and dice” CRM data to more effectively identify customers who are likely to buy, helping marketing and sales to better plan digital ads and micro-target campaigns.
• Predictive analytics — AI and machine learning, in tandem with statistical models and data analysis, can enable businesses to predict future customer behavior with confidence.

2. Sales and Marketing

Sales and marketing organizations can access powerful AI-driven marketing tools designed to help them improve efficiency and productivity. AI capabilities for these functions include:  

• Lead scoring and qualification — Qualifying leads saves time and money and allows sales teams to develop better-performing campaigns. AI-driven technology such as Invoca’s conversation intelligence platform, for example, uses machine learning to score phone leads, so that only high-quality leads form the focus of the marketing campaign.
• Behavior recommendations — AI solutions for sales and marketing can scan customer data to reveal patterns in browsing, buying, and other online behaviors that may inform marketing and sales recommendations to consumers.
• Natural language processing (NLP) — NLP, in conjunction with machine learning, is particularly useful for allowing marketers to analyze social media to better understand their audience’s buying intentions and tailor marketing tools and strategies accordingly.
• AI algorithms — Relevancy in ads is key to moving the customer along the buying journey. Algorithms allow marketers to target consumers with personalized, tailored experiences. For instance, ad content creators can use Invoca’s AI power to capture actionable insights from every inbound call, so they can efficiently retarget callers with relevant product ads on Google Ads.  

3. Contact Centers

AI in the contact center can capture a tremendous volume of phone calls from customer support and sales. It also provides a wealth of customer interaction data to improve the customer experience as well as inform agent training and performance. Future-forward call center operations use AI for:

• Recording and transcription — AI begins its role in the contact center with call tracking automation and recording. Using Invoca’s platform, for example, every call into the customer support call center is tracked, recorded, and transcribed in real time, creating an immediate record of the entire call. AI delivers analysis of each call, identifying patterns and keywords that help inform future marketing plans.
• Automated quality assurance — AI can also deliver automated quality assurance by dispassionately scoring calls and delivering those scores in real time — freeing up valuable time for managers and giving agents fair and standardized assessments of performance.
• Call routing and Intelligent IVR — AI can take repetitive and time-consuming but important tasks such as call routing off the hands of live agents. And AI-powered, conversational interactive voice response (IVR) provides an easier and more accessible experience for callers by allowing them to speak directly to the IVR instead of only pressing buttons to reply to questions and help route the call to the right destination. 

4. Supply Chain Management

AI tools and platforms can also streamline and strengthen links within supply chains — which supply chain managers sought to do long before pandemic pressures exposed critical weaknesses in these operations. AI can strengthen supply chain management in areas such as:

• Demand forecasting and inventory — AI can consume and number-crunch huge data dumps quickly, making it possible to predict periods of peak demand with more accuracy and confidence. Armed with this insight, companies can also manage inventories more efficiently, which is a big plus for logistics operations.‍
• Predictive maintenance — AI’s capacity to quickly slice and dice information from Internet of Things (IoT) sensors and other data sources can help businesses increase supply chain resiliency and reduce downtime.
• Route optimization and logistics — AI tools are continually pulling down, and learning from, data. This gives AI the ability to suggest alternative routes to drivers, just as apps like Waze and Google or Apple Maps do for users.
• Supplier management and risk assessment — AI can help managers analyze risks to the supply chain and manage relationships with suppliers more effectively to help ensure efficient purchasing. 

5. Human Resources (HR)

It may sound counterintuitive, but AI can help to improve the management of people in an organization, even in small businesses. Here are some of the ways that AI can enhance HR:

• Resume screening — Fifty-two percent of talent acquisition leaders say the hardest part of recruiting is screening candidates. Using automation and machine learning, AI can effectively screen more candidate resumes, far more quickly than any human.
• Candidate matching — AI can also help to identify the most qualified candidates quickly by analyzing each job description and scanning industry job boards and internal talent data.
• Skills assessment — AI-powered software can automate other key aspects of a company’s talent recruiting process, like assessing skills, to help increase hiring efficiency.‍
• Employee churn prediction — It typically costs more to recruit talent than to retain it. Using AI to help predict which employees might leave, or might be convinced to stay, can save businesses money and lessen the risk of critical staffing gaps.

6. Cybersecurity

AI has real value for businesses in terms of providing less costly, more effective, and more rapidly deployable and scalable platforms for fighting cyber risks and intrusions. AI can handle:

• Anomaly detection and behavior analysis — In an era of Zero Trust networks requiring strict identification of users who may be accessing the network from different types of devices, anywhere, anytime, AI can deliver complex, personalized security policies at scale.‍
• Malware detection and prevention — Huge amounts of data must be constantly analyzed to develop and update good malware detection software. AI can do the job faster.‍
• User behavior analytics — AI can analyze huge data sets of user behavior quickly to identify patterns that might indicate security breaches or other malicious or careless activity.‍
• Incident response and threat intelligence — NLP and machine learning capabilities in cybersecurity solutions can convert raw data into digestible intelligence that security teams can act on to respond to incidents and track threats.  

7. Business Intelligence and Analytics

Anywhere there’s data to be analyzed, AI’s use of NLP and machine learning can help. The following tools and technologies can help to enhance the work of teams responsible for a company’s business intelligence and analytics:

• Data preprocessing and cleaning — Converting unstructured data from various sources to a structured format is a time-consuming task. So, too, is scrubbing data to make sure it is accurate. AI tools can accomplish both tasks quickly and accurately.‍
• Data visualization and exploration — AI can also bring data to life by creating useful visualizations for users to review and incorporate into their decision-making.
• Predictive analytics and forecasting — Forecasting requires the analysis of huge amounts of data, which is definitely in AI’s wheelhouse.‍
• Natural language querying — Also known simply as NLQ, this process enables users to ask a question and a machine to understand it and provide a comprehensible answer. (Think of your AI companions Alexa, Google, and Siri.) 

5 Best Practices for Adoption of AI Tools in Business

Before you take the plunge and adopt an AI platform for your business, review these best practices for integration success, so you can get the maximum benefit from your new AI tools:

1. Assess Needs and Objectives

As we’ve outlined, AI tools can help users in many business functions, but you may have budget or user constraints. Conduct an honest assessment of your operations to identify key pain points and determine where AI can deliver the most significant impact. Then, prioritize AI implementation in those areas.

2. Select the Right AI Tools

Once prioritized, select only the tools that will address the needs you’ve pinpointed. Consider factors such as functionality, scalability, ease of integration and use, number of users, and vendor reputation. (A quick internet search can help you research options and find resources like an AI tools directory.)

3. Start with Small-Scale Pilots

Start small, deploying small-scale pilot projects to select users to test the effectiveness of AI tools in real-world scenarios before you consider scaling up. 

4. Provide Training and Support

Any investment in your tech stack is useless without proper training for employees who will use the tools. Invest in adequate onboarding and continue training so that your staff become effective (and enthusiastic) users of AI tools.

5. Measure and Track KPIs

Make sure you’re getting the most value from your investment in AI by regularly evaluating and analyzing key performance indicator (KPI) data. Those metrics will help you make data-driven decisions and identify areas for improvement.

Benefits of Implementing AI Tools in Your Business

Among the key benefits users can expect from smart investments in an AI platform are: 

• Automation and productivity
• Enhanced collaboration
• Cost reduction and resource optimization
• Improved customer experiences
• Predictive analytics and forecasting
• Fraud detection

Gaining a Competitive Advantage with Invoca AI Tools

Business tools built with natural language, machine learning, and other AI features are rapidly providing early adopters across many industries with a competitive business advantage. And one of the easiest and most rewarding ways to embrace AI tools for business is by minimizing repetitive tasks and digitizing analog functions. This brings a previously largely inaccessible trove of data into play for business — one that can be mined for operational, marketing, and sales purposes.

Invoca’s conversation intelligence platform is a good example of this. Prior to the development of contact center AI solutions, tracking and transcribing phone calls was an onerous task. So, too, was pulling customer and other data from those calls. With Invoca’s conversation intelligence solution, you can track, transcribe, and analyze every call, generating a wealth of actionable data that your business can use to streamline and improve operations and customer interactions. 

Just some of the ways Invoca’s customers use our platform include training customer service and sales staff with real-world insights from actual customer interactions, delivering automated quality assurance, optimizing digital ad and marketing campaigns, creating personalized experiences for customers, and reducing costs.   

Sample Invoca agent scorecard generated by AI

Invoca even helps marketers score phone leads, providing accurate attribution to marketing campaigns and allowing businesses to make smart budget decisions. Invoca’s Signal AI is also supercharging call analytics for marketers, allowing them to better understand and even predict consumer behaviors by mining data from phone calls.

The potential for AI in business is seemingly endless. And with solutions like Invoca already accessible to organizations of all sizes, there’s no need to wait for the future to start putting this advanced technology to work for your business. 

Additional Reading

Want to learn more about how you can use Invoca AI to drive better business results? Check out these resources:

• 5 Ways Marketers Use AI-Powered Call Tracking to Optimize Campaigns
• New Contact Center Report: AI Underutilized, but It's Key to Improving Performance
• How to Drive More Leads with AI-Derived 1st-Party Data

Jane Irene Kelly

The original version of this page was published at:  https://www.invoca.com/blog/harnessing-ai-tools-business-success