When we talk about artificial intelligence, we usually mean that it will be used on a grand scale – saving lives with artificial intelligence surgical tools, predicting historical events, driving autonomous cars, and so on. In the corporate sphere, business leaders are aiming for this, and artificial intelligence consulting is more in demand than ever. Not only does it help improve many business processes, but it also serves as an excellent tool for gaining customer loyalty and strengthening competitive advantage.
But what about small companies or startups? Can they use this new, confusing technology that even large corporations sometimes fail to implement correctly? Let’s look at the most effective uses of AI for small businesses and how it can help increase efficiency, improve employee experience, increase sales and make better business decisions.
Customer Relationship Support
Tracking interactions with each customer via the phone, email, or social media is a fundamental part of daily service. Customers today expect companies to know more about them than ever before. Providing personalized recommendations based on previous interactions has become the standard in any B2C industry, and answering questions before customers ask them often sets thriving companies apart from the rest. As customers become increasingly accustomed to pervasive recommendations on media streaming platforms and online marketplaces, their expectations rise, causing companies to adjust their approach.
Some people tend to believe that the complete replacement of salespeople with various AI-enabled tools is inevitable, which is, however, a very short-sighted viewpoint. One of the roles of AI here is to augment the unique skill set of humans by automating routine tasks.
Manual data entry is a known obstacle to satisfactory CRM implementation. It often leads to erroneous data, missing information, and wasted hours.
In contrast, AI-enabled tools can analyze text and audio data from customer interactions and automatically add that information to CRM.
The capabilities of AI in CRM are vast. For example, Einstein AI can also identify the intent behind text messages using natural language processing (NLP). This alone can significantly improve efficiency and speed decision-making by prioritizing “hot leads” and first giving them the most attention.
By gathering information about the customer from various sources, including data on site views and prior interactions, AI can deliver valuable contextual suggestions to the sales rep who is about to answer an incoming call from a customer. Going one step further, the AI can predict which actions will lead to a transaction. With AI’s ever-improving algorithms, recommendations become more accurate and the rationale for those recommendations more explainable, circumventing the AI black box problem.
Automating customer interactions
We also have thousands of less complex customer requests. For example, many customers double-check restaurant hours, even if they are clearly listed on the official website or social media. Thanks to recent advances in chatbot development, such questions can easily be answered without human resources.
Helping the human resources department
Ironically, at the heart of HR is the word “human.” Typical HR tasks, such as evaluating employee performance or assessing job applicants’ skills, come down to careful analysis and only then making a decision. AI can again reduce the time it takes to find the most suitable candidates by automatically processing thousands of applicants and prioritizing them based on specific parameters.
Google’s Hire applicant tracking system, especially relevant to small and medium-sized businesses, is designed to reduce time-consuming tasks by highlighting the most critical words on resumes, automatically scheduling interviews, and calling candidates without manually entering their phone numbers.
From a hiring perspective, AI can also help write better job descriptions. In the case of recruitment, this means “attracting exactly the candidate we’re looking for” or “expanding the pool of candidates by using broader job descriptions.”
The software collects data from various popular business tools, including G Suite, Slack, and Office 365, and analyzes it to uncover hidden patterns affecting employee satisfaction.
Proper cash flow management
According to the Bureau of Labor Statistics, 20% of small and medium-sized businesses fail in the first year and 50% yield after five years. While these numbers don’t seem so aspirational, small companies often make the same mistakes. Cash flow is the second most cited reason for failure among small and medium-sized businesses. This area remains outside the control of many business owners, leading to detrimental mistakes such as deferring loan payments, failing to predict creditworthiness, and misunderstanding sales trends.
AI can be that rational, impassioned financial assistant, able to predict cash flow risks and help mitigate them. For example, the QuickBooks app uses AI to provide cash flow recommendations based on 90-day forecasts. It also offers advice based on accurate data, whether it’s a short-term loan that could save your business or a strategic employment recommendation.
Gaining a competitive advantage with AI
Many competing businesses frequently operate in the same niche with a very specific target demographic. Every client has the ability to make a difference. Competitive advantage in similar products or services extends much beyond basic marketing efforts and pricing modifications. Conducting a comprehensive competition study is the first step toward establishing a true competitive advantage.
Crayon, for example, uses artificial intelligence to transform the most critical data from companies’ Web sites into meaningful reports. Machine learning combined with natural language processing allows Crayon’s software to filter the data and distill it into insightful insights. These reports are then used to create effective marketing and sales strategies. It eliminates manual research, giving managers more time to develop strategies and make data-driven decisions.
Debunking myths about artificial intelligence
Small businesses rarely research non-traditional solutions like AI. The confusion that AI causes is understandable. Not only does this technology require in-depth research to understand fully, but it remains largely unexplored in many niches. If a critical player in an area does not use new technology and succeed, others are not ready to adopt it.
However, when implementing potentially revolutionary solutions that require sufficient training and flexibility, this “following the leader” situation is much less likely for small businesses. However, the underutilization of AI tools among SMBs makes this technology so powerful for gaining a competitive advantage. Now let’s look at some common myths small businesses hold about this technology.
Implementing AI is too expensive
While this is often true for corporate and government organizations, implementing AI for small businesses is much less expensive. Implementing AI in businesses is relatively astronomical because their business models often require regulatory compliance, carefully developed software, specially trained AI algorithms, management of sensitive information, and a dedicated development team.
Small businesses don’t need to invest in a development team because many off-the-shelf AI solutions are already on the market. Even if a small business needs a customized approach, it is likely to use open-source machine learning frameworks, which implies a reasonable price.
Finding out the reason for implementing AI is an essential part of your implementation plan. In many cases, the best solution is to choose a non-AI approach to a particular problem. How soon will implementing an AI solution provide a return on investment? A common trap that ambitious small businesses fall into is implementing AI to “find new ideas.” But insight will never directly increase your sales or market reach, but solutions based on that insight will.
Next, create a proper data management infrastructure. Hiring AI developers without a clear data plan is a sure way to waste money and resources. What’s more, data-driven technology will sooner or later lead to the destruction of your niche. If you are prepared for this revolution, and all data is clean, structured, and consolidated in one place, you will gain a long-term competitive advantage.
If there is no specific use case, there is no need to rush into implementing AI right now. Instead, focus on research and start preparing your organizational culture and data for the inevitable arrival of mainstream AI.