Today, as the hype around AI remains high, many companies are eager to integrate this technology into their processes without a clear understanding of the goals behind such initiatives. These approaches to AI business integration often fail to deliver the desired results and can lead to a range of undesirable outcomes, including significant financial losses.
That’s why if you are considering implementing AI, the first task should be to carefully examine all aspects of the matter. Starting with this, you will be able to define the right strategy, ensure a smooth introduction of AI, and maximize the efficiency of this technology.
In this article, we are going to share practical recommendations for AI integration for small and medium-sized businesses (SMBs). These tips will help you better understand the peculiarities of this process and find the best approach that will work in your case.
AI for SMBs: Is it really worth investing?
Approaches to any tech projects at SMBs quite differ from those that are typical for enterprises and larger organizations. Smaller companies traditionally have smaller budgets and fewer resources, which means that they can’t concentrate on too many things at once. That’s why they need to allocate enough time and force to the research and planning stages.
When they do not have the required expertise in-house, it will be a feasible idea to turn to AI integration consulting services. Though such services are traditionally provided on a paid basis, such investments will fully pay off in the near future. Thanks to professional help, companies can get a clearer vision of their own goals and prospects of integrating artificial intelligence.
Moreover, they will be able to define the key priorities that they should focus on during the initial stages of AI integration in business processes. This will also help them avoid unnecessary expenses and minimize financial risks.
But if a company has limited resources, does it really make sense to think about the introduction of AI? Well, of course, it depends. In general, it can be highly beneficial. Let’s consider the top factors that drive the adoption of artificial intelligence today.
Benefits of AI tools for SMBs
Cost efficiency
Businesses can apply AI to reduce operational costs. This can be achieved by automating repetitive tasks, optimizing workflows, and enhancing resource allocation. For example, ML algorithms can analyze sales data to suggest inventory optimizations or identify cost-saving opportunities. AI-powered chatbots can handle customer inquiries 24/7. As a result, businesses can avoid the need to maintain large dedicated customer support centers.
Apart from this, artificial intelligence models can help companies streamline operations and minimize risks of human errors, which can lead to financial losses.
Improved customer experience
Chatbots, personalized recommendations, and predictive analytics are gradually becoming a standard across various domains. And the reasons behind this trend are quite obvious. First of all, they facilitate a lot of tasks for businesses themselves. And secondly, they can significantly enhance the customer experience.
AI can provide businesses with valuable insights that help them tailor their services or products based on real customer needs. Moreover, the personalization of content and recommendations also greatly contributes to the growth in customer loyalty.
Data-driven decision making
AI can process massive amounts of data to extract meaningful insights that could be unnoticed when data is analyzed exclusively by humans. Such insights can enable better decisions across all aspects of the business, including marketing strategies and production plans.
Scalability
AI solutions can successfully grow together with companies and assist them in scaling. How is it possible? They provide automation and intelligence that can handle increased workloads without a proportional increase in human resources. According to the study published by PWC, it is possible to double the workforce only by implementing AI agents.
Competitive advantage
Though tech giants and large organizations are usually among the leaders of the tech revolution, the adoption of AI among SMBs has already started as well. However, many SMBs are still hesitant about implementing AI. It means that it is still not too late to jump on the bandwagon and leverage all the new opportunities that this technology opens. Being an early adopter of AI can help small businesses stay ahead of the curve and compete with larger enterprises.
Such benefits may sound quite inspiring. Nevertheless, before making a final decision, it is always necessary to analyze not only the advantages of AI but also your business goals, budget, and overall readiness to adopt new technologies.
Key things to consider before AI integration in business
Initial costs
The implementation of AI solutions traditionally requires significant upfront investments in software, hardware, and training, especially when it comes to custom systems.
If a company is not ready to invest in custom development, today there are quite a lot of more affordable, cloud-based AI tools. Nevertheless, in this case, it is vital to understand that such tools may not fully meet some specific business needs. As a result, the efficiency of their implementation can be lower than expected.
Skill gaps
SMBs may lack the technical expertise to implement and manage AI systems. And quite often it can be rather challenging for them (and even not feasible) to change their corporate structure and hire new specialists. Of course, in this case, they can establish cooperation with an AI integration company that provides all required tech support. But it is important to calculate all the associated costs beforehand and plan the budget smartly.
Data requirements
Any AI system relies on data. If your business lacks sufficient or clean data, the effectiveness of AI may be limited. That’s why one of the most important things to verify is whether you have high-quality datasets that can be used for your solution. You can use your own business info, as well as publicly available databases. Nevertheless, if your business processes are too specific, generic datasets won’t be of great help.
Integration with existing systems
Making your new AI tools work seamlessly with your current infrastructure can be a difficult task (especially if you still rely mainly on some legacy systems introduced many years ago). Such cases may require additional efforts and resources.
Traditionally, AI integration services include professional help in this aspect. However, businesses should be ready to face situations when legacy systems need to be fully modernized amid their plans to implement AI tools.
ROI uncertainty
The return on investment for AI projects may not be immediate. It’s important to set realistic expectations and measure outcomes over time. You may start noticing changes practically instantly after the introduction of new tools. However, tangible results and impact on your profits may be seen not as fast as you initially expected.
It’s interesting that when it comes to AI projects, for many organizations, ROI is not always the primary driver of AI investments. According to a study conducted by IBM at the end of 2024, 41% of IT decision-makers who participated in the survey admitted that their organizations are equally innovation-driven and ROI-driven.
AI business integration: Key areas to explore for SMBs
As for the zones where AI can be integrated, it is vital to mention that there can be two different approaches to introducing this technology:
- AI augmentation (when AI tools are applied to help people and empower teams with new possibilities);
- full AI automation (when AI tools are expected to replace humans).
Speaking about this, we should highlight that the first approach may include automation as well. However, unlike the second one, it doesn’t presuppose the full exclusion of humans from business workflows. Yes, thanks to the deployment of new solutions, businesses may have a chance to reduce their human labor force. But people are still in the center.
As for full AI automation, this concept is rather radical. Those businesses that want to adopt it should be ready to make their processes run with zero workers. Though some enterprises are already trying to build such factories, at the moment, there aren’t successful examples of the realization of such projects. Right now, the technology is simply not ready for it. Will this approach be massively adopted by SMBs later? That’s the question that the business community will have to answer in the future.
Today, it makes sense to talk about AI augmentation projects, when this technology is used to enhance the efficiency of human efforts. Let’s have a look at the key areas for AI integration by SMBs.
Customer support and interaction
Today, a lot of businesses rely on AI chatbots and virtual assistants to automate their interactions with customers and reduce the load on their client support teams. Chatbots can perfectly cope with standard inquiries and redirect questions to managers if human participation is required.
Moreover, AI can be used for sentiment analysis. Special tools can monitor customer feedback and reviews to provide insights into what people really feel about the offered products and services.
Marketing and sales
As Tensorway acts as an AI integration company, we know that quite often companies have requests to implement digital tools for such business functions as sales and marketing. Specialists in these spheres have to deal with huge volumes of continuously changing data. As these volumes grow, it can become absolutely impossible to process them manually and timely react to all the changes.
Here’s when AI can come into play. Predictive analytics tools can identify potential leads and forecast sales trends. The gained insights can help salespeople to find the right approaches to driving sales.
Generative AI can be applied to create visual and textual content for marketing needs.
At the same time, special tools can analyze customer behavior and preferences to send personalized emails in the framework of marketing campaigns. Moreover, AI tools can help to automate work on social media. For example, they can schedule, optimize, and analyze posts across different platforms.
Finance and accounting
Finance and accounting are also among the spheres that include a lot of manual work. Due to the specificity and complexity of processes, a lot of them are prone to mistakes. AI can help to facilitate a lot of tasks for specialists and reduce the number of possible errors.
For example, AI-driven tools are used to track expenses, generate financial reports, and automate payroll. They not only streamline such processes but also let people concentrate on more complicated and strategic tasks that require their creativity and critical thinking.
Apart from this, AI can forecast financial trends, as well as evaluate credit risks for businesses offering financing or installment payments.
HR and recruitment
Instead of onboarding new recruiters and HR specialists, today a lot of businesses turn to AI integration consulting and introduce powerful AI tools based on their needs. That’s a really working and cost-efficient approach.
For example, you can introduce AI tools to automate resume screening and identify top candidates based on the skills and experience described in their CVs. Automated screening of resumes makes the process much faster and more efficient. Manual screening can take really a lot of time. Instead of just looking through tons of CVs, recruiters can dedicate their work hours to communication with candidates or any other tasks that can’t be assigned to artificial intelligence.
This technology can be quite helpful in corporate learning and onboarding training. It can adjust the materials to the personal needs of each employee to make the learning process much more efficient and result-oriented.
Another use case where AI can be of great help is the analysis of employee feedback.
Today a lot of businesses introduce various forms to collect employees’ opinions. AI can not only analyze and visualize the results of such surveys but also provide actionable insights with recommendations for improving workplace satisfaction.
Cybersecurity and data protection
What artificial intelligence and machine learning models are really good at is detecting patterns and identifying any signs of abnormal behavior and suspicious activities on different networks and apps. These capabilities can be applied to increase the level of security and data protection at your company.
AI tools successfully detect even the slightest signs that can be an indicator of fraudulent activities. After that, they can immediately send notifications to the relevant specialists and/or take the required measures. Thanks to this, companies react to cyber threats and prevent them even before they escalate.
Apart from this, AI systems can conduct automated checks to ensure regulatory compliance and enhance authentication.
Of course, that’s not the full list of all the possible use cases and areas of application where artificial intelligence can bring value to your company. Each industry and each domain has its own specific processes that can be upgraded or fully revolutionized with this technology.
For example, by following this link you can explore how artificial intelligence can be used to optimize various tasks for eCommerce businesses.
AI business integration: What to begin with
As a rule, the implementation of AI in business is a complex project that encompasses various aspects of a company’s operations. Therefore, before developing AI-driven tools or starting to use any ready-made systems, you should be well prepared for this.
Building a strong foundation for it is crucial for ensuring the successful introduction of AI technologies and maximizing benefits from them. Good strategic planning is a must if you want this integration to be smooth.
Based on our practical experience in providing AI integration services to SMBs and larger organizations, we have prepared the following step-by-step guide for businesses that are just starting this journey.
Step 1. Identify clear goals
First of all, you need to determine your key pain points. In other words, you should find the areas of your business that could benefit most from AI and prioritize them. For example, you may decide that you have the most issues with customer service and you want to address them first. Or maybe after a close analysis, you will choose marketing to start with. There isn’t a one-size-fits-all formula. Each case should be considered individually. And that’s exactly what you can get in the framework of professional AI integration consulting.
When the key points are defined, you need to set goals for your tech innovation. You should have measurable objectives that you can track. We recommend you apply the SMART principle to goal setting. It means that your goals should be:
- Specific (The goal should be clear);
- Measurable (It should be tracked and/or quantified);
- Achievable (Your target should be realistic);
- Relevant (It should align with broader business objectives);
- Time-bound (There should be a clear deadline).
For example, instead of formulating your goal as just “to reduce customer service costs”, you can put it as “to reduce customer service costs by 20% within six months by implementing AI-powered chatbots and automated ticketing systems, while maintaining a 90% customer satisfaction rating”.
Step 2. Prepare technical infrastructure
It is impossible to move your project forward if it can’t be implemented from a technical point of view. If you do not have tech experts with relevant skills in-house, you can hire an AI integration company. Its specialists will conduct the assessment on their own.
Here are a couple of things that you should take care of in advance:
- Cloud computing. It’s highly recommended to move your solutions to cloud-based platforms for scalability and cost-effectiveness.
- APIs and integrations. You need to verify whether your existing systems, such as CRM or accounting software, can integrate with AI tools.
- AI-ready hardware. Not every piece of hardware is ready for working with AI tools. If you are going to deploy AI on-premises, you may need to invest in hardware like GPUs for advanced AI tasks.
Step 3. Assess your data readiness
As we have already indicated, the quality of data is one of the most fundamental factors that will define the efficiency of your AI system functioning. That’s why before introducing any solutions, you need to pay attention to the quality of data that you can use for training. Make sure that your data is clean, structured, and accessible.
It will be also reasonable to invest in secure, scalable storage solutions. Today, a lot of businesses prefer cloud platforms like AWS, Google Cloud, or Azure.
Don’t forget about such an important point as regulatory compliance. We recommend that you implement data governance policies to maintain security and compliance.
Step 4. Develop AI talent and expertise
Though AI itself can’t be named a very new technology (some studies were conducted even several decades ago), its mass adoption has started comparatively recently. As a result, it’s quite natural that there are not many specialists with expertise in AI integration and maintenance.
When you are starting to work with artificial intelligence, you need to have professionals with relevant skills by your side. Here you have several options:
- To upskill employees. It can be a good idea to invest in professional training for your tech employees. They may be taught how to work with AI systems for your needs. As for other specialists, you should also train them on AI basics and tools relevant to their roles.
- To hire new specialists. You can also bring in new data scientists, AI engineers, and business consultants if needed.
- To collaborate with vendors. A lot of SMBs opt for this option. To optimize their expenses at least at the initial stages of the project realization, they partner with an AI integration consulting and/or development company.
Step 5. Choose the most appropriate AI tools for your goals
Here, again you have several options. The choice between them should be based on your individual needs, requirements, expectations, and budget.
You can either implement off-the-shelf solutions or develop your own custom tools.
Both of these approaches have their pros and cons. For example, the use of pre-built products traditionally requires significantly smaller upfront costs (your expenses will be mainly related to your infrastructure) than custom development.
Nevertheless, only custom systems can be fully tailored to your specific business processes. As a result, the efficiency of such solutions will be higher.
Sometimes, SMBs that have limited budgets start with low-cost off-the-shelf tools and gradually proceed to the creation of their unique systems.
AI integration strategies: What you should know about them
When the main preparations are over, your data and infrastructure are ready, and you already know what tools you will use, it’s time to think about the strategy that will guide you.
We offer you to have a look at the strategies that are most commonly applied among SMBs.
Phased integration
This approach presupposes gradual implementation. In this case, AI is introduced in stages, moving from low-risk to high-risk and from high-impact to low-impact areas.
Businesses that have limited resources often choose this strategy. It includes the following steps:
- Identification of a specific problem or process to address;
- Implementation of a pilot project;
- Result analysis;
- Approach enhancement;
- Scaling.
Phased integration
This approach presupposes gradual implementation. In this case, AI is introduced in stages, moving from low-risk to high-risk and from high-impact to low-impact areas.
Businesses that have limited resources often choose this strategy. It includes the following steps:
- Identification of a specific problem or process to address;
- Implementation of a pilot project;
- Result analysis;
- Approach enhancement;
- Scaling.
End-to-end integration
With this approach, businesses implement AI across multiple business functions simultaneously. This integration type is less popular among smaller companies than the previous one. However, if you have sufficient resources and a very clear AI integration plan, it can be chosen as well.
Key phases:
- A thorough assessment of all business processes;
- AI solution deployment across the chosen areas;
- Integration between systems and departments.
Embedded AI
The previously discussed approaches were focused on introducing new solutions. Unlike them, this strategy concentrates on integrating AI features into existing software that your business already uses.
For example, you can introduce AI-enhanced features for your accounting software or implement AI-powered analytics in Google Sheets.
This can be a good option for companies that have well-established workflows and powerful systems that can be enhanced with AI.
AI-first digital transformation strategy
This strategy is based on the full integration of AI into the core of business operations. AI becomes the foundation for decision-making, process optimization, and customer engagement.
At the same time, apart from relying on traditional AI integration services, businesses need to do some serious “homework” on their own. They need to adopt a data-driven culture. Data and AI insights should become the main factors guiding strategies and operations. Of course, such changes take time. But they also bring their fruit.
AI-driven innovation
In this approach, companies use AI to create entirely new products, services, or business models. It means that in this case, artificial intelligence is perceived not as a supportive tool but as a central component of new offers.
AI-powered subscription services or smart devices with embedded AI can be named among the examples of the implementation of this concept.
Of course, this strategy is not suitable for a wide range of companies. It is appropriate only for those who have plans to introduce new products or services and have resources for such initiatives.
AI for SMBs: Future trends
AI business integration is gradually becoming a new trend among small and medium-sized businesses. But what’s next? Here’s what we expect to observe in the future.
Democratization of AI tools
Today such tasks as AI solution development and ML model training require specific skills and knowledge. It means that only people with relevant expertise can perform them. Given the lack of such specialists and the complexity of these tasks, it is not surprising at all that AI solutions today are quite expensive.
Nevertheless, it is expected that in the future the entry barrier to the AI space will be reduced. In other words, even people without specific tech skills will be able to contribute to the creation of AI solutions.
It will be possible thanks to the growing adoption of no-code and low-code platforms like Google AutoML or Zoho Creator. Such platforms usually have drag-and-drop interfaces. As a result, some new functionality or workflows can be added to your project with a couple of clicks, instead of manual coding.
Thanks to this, AI tools are expected to become more affordable and accessible to SMBs.
AI-powered hyper-personalization
Already today personalization is among the highest priorities for many B2C companies. Nevertheless, with further AI business integration, this personalization will skyrocket to a new level.
AI can analyze customer behavior in real time. It means that AI-powered platforms are able to deliver ultra-personalized recommendations and experiences tailored to the needs that a person may have at this very moment.
For instance, an AI-driven eCommerce platform can offer dynamic pricing and personalized product recommendations. All this can ensure higher engagement, better customer retention, and improved conversion rates.
Voice and conversational AI
Voice and conversational AI can fully transform how businesses interact with customers. These technologies leverage natural language processing (NLP) and machine learning to enable human-like interactions through voice assistants, chatbots, and other conversational interfaces.
Voice AI tools are designed to enable users to interact with systems using voice commands. Such solutions can ensure hands-free experiences for users and increase the inclusivity of platforms.
Meanwhile, conversational AI powers chatbots that can engage in human-like text or voice-based conversations with users.
It is also predicted that tech advancements will allow businesses to introduce highly powerful multimodal AI apps. They will combine voice, text, and visual interfaces, which will guarantee richer interactions.
Apart from that, one of the next stages of the development of AI technologies will be the introduction of emotional AI. Such tools will be able to detect and respond to customer emotions for more empathetic interactions.
Wrapping up: Is your business ready for the AI revolution?
AI today is not only one of the most trending technologies but also one of the most influential. This indicates that AI integration is gradually shifting from being an innovative tendency to becoming a necessity. This is especially relevant for businesses that want to stay afloat in a highly competitive market and adapt to constantly changing customer demands.
Although it is usually tech giants and enterprises with large budgets that become pioneers in adopting new technologies, small and medium-sized businesses are also starting to enter the game.
Of course, AI implementation processes at SMBs differ significantly from those at large enterprises. Unlike corporate giants with vast resources and dedicated AI teams, small and medium-sized businesses need to take a more strategic and cost-effective approach. This explains their high demand for AI integration services.
Moreover, SMBs typically integrate AI incrementally, starting with automation in separate functions before expanding into more complex applications. This flexibility allows them to adapt quickly while ensuring AI investments align with their business goals.
Regardless of your exact plans, the key to successful AI adoption lies in a clear vision, a solid foundation, and a well-planned integration approach. Assess your current processes, define your goals, and explore scalable AI solutions that can address your business needs.
Are you looking for a tech partner that can provide you with professional AI integration services? At Tensorway, we are always at your disposal. With our robust expertise in this sphere and openness to new trends, we will be able to offer you the best approach to implementing this technology in your processes. Contact us to get more details!
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