Most business owners are understaffed. Yet, they have to worry about replying to emails, tracking deliveries, and making sure that ad campaigns go live on time. For SMBs, competing with enterprises is tough.
Sure, intelligent process automation (IPA) and robotic process automation (RPA) can help, but only to an extent. But are these business automation software enough for an evolving market? Otherwise, you'll need to consider applying AI in business process automation.
AI will push business process automation beyond the rule-based workflow they’re limited to. Let’s say you’re replenishing stocks only after your inventory management software alerts you that they’re running now. What if there’s a delivery gap because of factors you can’t control? With AI, you can predict the demand and consumption to manage your inventories more efficiently.
That’s just one example of what you can achieve with generative AI, natural language processing (NLP), and machine learning technologies.
In this guide, Oleh Komenchuk, a machine learning engineer at Uptech, and Andrii Bas, Uptech’s co-founder and AI expert, share their thoughts on AI automation for small businesses.
We’ll also explore use cases, technologies involved, and how to automate business processes with AI in your company. More importantly, you will learn how AI-powered business process automation can bridge inefficiency in other parts of your business.
Let’s begin.
What is the role of AI in business process automation?
Business process automation helps business owners streamline repetitive tasks. This way, they can focus on high-value activities. AI, or specifically generative AI, introduces cognitive abilities into business processes. In other words, instead of merely automating workflows, you can improve how existing BPA software operates by analyzing business data it collects.
Imagine not spending time entering customers' details into the CRM. Instead, you use computer vision technologies to extract key details from documents/scans. As AI becomes more prominent in business process automation, you can anticipate more of such impacts on your business.
Enable smarter decision-making
AI can learn to make decisions as humans do. When applied to business process automation, it allows you to identify patterns and trends that normally escape human observation. You can then use the insights to minimize risks when making business decisions.
Example: SMBs can apply predictive analytics to manage their inventory levels accordingly.
Automate complex tasks
BPA solutions excel at automating routine tasks, but they struggle with workflows that involve complex reasoning. For example, BPA cannot handle unstructured data like raw social media feeds efficiently. That’s where AI will be helpful. AI can adapt and learn efficiently, such as analyzing sentiments from customer chat logs.
Example: You can use AI to automatically draft personalized email replies instead of writing them manually.
Improve scalability
One reason business owners implement business process automation is to scale their growth. With AI, scaling your business has even less friction. Instead of hiring more employees to tackle mundane tasks, you can operate with a leaner, high-performing team.
Example: AI can help you screen and shortlist candidates by analyzing resumes they sent.
Enable continuous improvement
Conventional business process automation, while helpful, isn’t self-adaptable. Such systems can only function within the rules they’re confined to. Conversely, AI technologies like machine learning can learn, adapt, and evolve over time. As AI modules learn more from repeated usage, they become more consistent and accurate when assisting you in business operations.
Example: AI allows you to run more targeted marketing campaigns by analyzing customer behavior.
Allow business-wide integration
AI further augments BPA’s role in streamlining your business operation. With AI, you can have more visibility into how one business unit interacts with others. AI allows various software to exchange data more efficiently and according to the context of the respective business users.
Example: With AI, the customer team can receive timely alerts if the procurement department has difficulties securing certain products from suppliers.
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AI for Business Automation: 15 Solutions To Consider
Business process automation can greatly benefit from integration with AI. The question amongst business owners is, how does it impact their workflow? We share several AI business automation ideas that can solve some of your concerns in juggling daily operations.
1. Assist customer support
You can integrate AI with business process automation to improve the response rate to customer inquiries. Rather than channeling all inquiries to your support team, you can filter them with an AI chatbot. The chatbot will resolve common inquiries, leaving your support team to handle the more complex ones. Shorter, personalized, and prompt responses often lead to better customer satisfaction and repeat purchases.
2. Analyze customer sentiment
AI can shed light on why customers don’t buy or are dissatisfied after engaging with your brand. When integrated with business automation, AI can analyze surveys, emails, social media feeds, and other correspondences to gauge how customers feel about your brand. You can also use AI to analyze possible causes leading to their current sentiment and craft appropriate responses.
3. Improve inventory management
AI-enabled BPA can track inventories, predict supply vs. demand, and recommend the optimum stock level for business owners. It helps you prevent overstocking or running out of stocks because of oversight, market fluctuation, or other unforeseen circumstances. With increased visibility, you can prevent disruptions that could negatively affect customer satisfaction and brand image.
4. Accelerate invoice processing
Many SMBs manually key invoice details into their invoicing system to issue payments. If you’re still stuck with such a tedious process, integrating AI with invoicing software can expedite the workflow. AI can identify and extract specific information, such as the vendor’s name, date, and price, from individual invoices and consolidate them in the invoicing software.
5. Enable financial forecasting
AI automation for small businesses can help owners forecast their financial standing more accurately. Generative AI technologies can analyze vast financial data, market trends, and other factors to help manage your budgets later. BPA, powered by AI, provides financial insights that help you avoid cash flow issues and other setbacks due to bad financial decisions.
Learn more about Generative AI in banking in our guide.
6. Streamline contract management
Small business owners spend valuable time drafting, reviewing, and filing contracts when striking up partnerships. By automating contract management with AI, you can avoid mistakes and ensure contracts are created to legal standards. Rather than inspecting stacks of legal contracts, AI can scan and extract specific legal terms from the documents and inform you of your risks when conducting due diligence.
7. Coordinate logistics
Some SMBs are involved in the supply chain industry, which requires tight coordination to ensure timely goods delivery. Instead of entirely depending on human supervision, AI can take over tedious and complex coordination. With an AI-automated system, you can optimize fleet paths, perform preventive maintenance, and improve overall efficiency.
8. Detect accounting anomalies
For small business owners, balancing their accounts and complying with audit laws are important. With AI, accounting software can be more intelligent and robust. For example, generative AI can detect anomalies in the accounts so you can quickly address the issue.
9. Provide real time price quote
SMBs in eCommerce strive to price their products competitively. However, they face challenges in determining the best price points because of the varying factors involved. AI, when integrated with eCommerce platforms, can recommend an optimum price in real time after analyzing various price factors. You can also use AI to provide a customized price quote more effortlessly based on your customer’s spending history and past interactions.
Explore new possibilities that AI brings for e-commerce.
10. Automate marketing campaign
Your marketing campaign will be more targeted and precise with AI involved. You can segment customers based on their spending behaviors, demographics, and preferences more easily than ever. Also, AI can analyze data in real time and create personalized messages that target specific customer groups. This, subsequently, helps you increase engagement and conversion.
11. Increase sales efficiency
With AI, you can have more clarity in your lead acquisition process. AI can assess potential customers and score them according to their likelihood of converting. This way, you know which segment needs more time to nurture and which has a higher chance of buying. On top of that, you can use AI to determine the best price, package, and discount for specific buyer groups to maximize profitability.
12. Assist in talent recruitment
Often, small business owners participate directly in the hiring process. They spend valuable time going through dozens of resumes, reaching out to potential candidates, and arranging for interviews. AI can automate the recruitment workflow by screening applications and selecting candidates that meet specific requirements. A fully integrated AI-human resource management solution can also make onboarding more effortless for successful candidates.
13. Support market research
SMBs have the advantage of being agile and quickly adapting to market changes. But to do that, you need to minimize risks when making business decisions. Applying AI in business process automation allows you to analyze market trends, customer data, and competitors at scale. By covering more market variables, you can strategize more confidently as you innovate and expand your business.
14. Ensure regulatory compliance
Some businesses operate in very highly regulated industries. For example, if you own a clinic, you must comply with HIPAA or similar local acts. Augmenting business process flow with AI can detect non-compliance in data collection, transactions, and other business activities early on. This lets you take prompt corrective measures and avoid costly fines.
Here's how generative AI benefits healthcare industry.
15. Strengthen data security
When you digitalize your business, it’s important to prioritize data security. Otherwise, you will be susceptible to cybercriminal attempts and suffer from data breaches. AI-enabled security solutions can automatically scan for threats and vulnerabilities. They reduce gaps that bad actors can exploit to harm your business.
AI Business Process Automation: Real Cases
What we share above are not mere theoretical possibilities of AI in business automation. SMBs worldwide have adopted AI in their business workflow and experienced positive results. These are some interesting examples we found.
1. Investment: WealthFront’s Robo-advisor
WealthFront is an investment firm that provides AI-assisted advisory. As we know, making investment decisions requires thorough consideration of large volumes of time within a short time span. WealthFront uses an AI-powered investment assistant to help human advisors make the best decisions.
The robo-advisor analyzes volumes of historical investment data to identify opportunities that traditional methods might overlook. This machine learning-powered tool can also alert human advisors when investment allocations go beyond the specified limits. More importantly, robo-advisors relieve human advisors from mundane tasks so they can focus on strategic work.
2. Fashion: Blend’s personalized recommendations with AI
Blend is a UK apparel startup that uses AI creatively to help shoppers find clothing that interests them. While many retailers offer personalized recommendations by studying the customer’s purchases, Blend went a step beyond. They recognized that analyzing historical data alone cannot predict user behaviors when trends change.
So, Blend uses AI to analyze how to interact with their apps. Every product or video a shopper likes, or taps in the feed becomes valuable data for the AI model. The app also recommends apparel based on the user’s size and other preferences.
3. Fintech - Kabbage’s AI-powered loan platform
Kabbage offers loans to small business loans via an AI-enabled platform. It accelerates loan applications by applying machine learning to evaluate and score applicants according to their credit risk. Imagine getting your approval within days, instead of weeks. Plus, Kabbage can offer lower rates than conventional lending institutions with its AI engine.
4. Hospitality: Edwardian Hotels London’s AI chatbot
Edwardian Hotels London wanted to personalize the guest experience without overwhelming their staff. They implemented a generative AI chatbot, Edward, that can interact with guests. Rather than expecting guests to key in specific commands, the chatbot applies natural language understanding technologies to effortlessly take requests from guests. And if it couldn’t resolve the request, the chatbot would channel it to a human concierge.
While Edward was transformation with its AI technologies, it was not the first app the the hotel chain built. Throughout the years, Edwardian Hotels London has built 30+ apps, including a guest check in mobile app.
How to implement AI in business processes: 8 Key Steps
AI can benefit small and medium businesses in many ways. Of that, we’re convinced. But as a business owner, how do you start? We share the steps we take to help SMB owners integrate AI to automate their business processes.
Step 1: Align AI integration with business needs
Often, integrating AI with company-wide business processes is not feasible. If you do that, you’ll need to invest more funds and face a more complex migration process. Besides, not all business workflow will experience massive benefits when integrated with AI.
Instead, it’s better to be selective about which workflow to integrate with AI. For example, if you’re running a customer call center, building a generative AI chatbot to automate call response is more beneficial than automating content creation.
Step 2: Choose the right AI model
There are different AI models that power today’s generative AI applications. At Uptech, we integrate BPA with models like GPT 3.5, GPT 4, Alpaca, and Stable Diffusion. If you want to streamline your customer support by automating email replies, you’ll need a large language model like GPT. However, Stable Diffusion is better for image analysis, image generation, and other computer vision tasks.
Regardless of which model to choose, it’s important to evaluate it for precision, accuracy, and recall indicators. Usually, business owners engage AI developers like Uptech to assist them because AI-BPA integration requires deep technical expertise.
Check this list of top 10 AI development companies.
Step 3: Prepare training data
You can’t integrate the AI models until you train them. Even if they’re capable of producing realistic responses, AI models cannot provide information related to your products or services. That’s why training the model with data specific to your business is important.
At this stage, we’ll help you to curate data from various sources to train the model. For example, if you want to build a healthcare virtual assistant, you’ll need to collect data from patient registration, chat logs, and other sources. Then, we clean the data to ensure the training sample is free from duplicates or outliers.
While doing this, it’s important to comply with acts like HIPAA and protect patient’s privacy. Throughout the model training, we work closely with domain experts to produce high-quality data without compromising ethical principles.
Step 4: Train the model
We’ll be frank upfront. Training the model is expensive and often unnecessary for most business use cases. Instead of spending an exorbitant amount of money and time, it’s better to fine-tune a foundational model. Foundational models are pre-trained with massive datasets, which require minor adjustments to fit into your business application.
Let’s say you want to create an AI assistant capable of analyzing user sentiment from customer chat. Instead of training a model from scratch, you can fine-tune a model like GPT, Bert, or a simpler machine learning model with training samples. Besides enabling the model to perform business-specific tasks, we also apply a human-in-the-loop mechanism to ensure the model produces helpful and appropriate responses.
Step 5: Integrate with your business application
While we’re fine-tuning the model, our app developers prepare your application for integration. We need to ensure that your app is designed to exchange data reliably and safely with the model. More importantly, your app must be able to scale along with usage growth. Otherwise, we’ll need to modify, improvise, or rebuild the app.
Once both the app and model are ready, we integrate them. This involves hours or weeks of coding, testing, and revising. As we integrate your app with AI, we apply measures that make your app secure, scalable and user friendly. Ultimately, your users must feel safe and not intimidated by the changes.
Step 6: Test and revise
We won’t launch your AI-integrated app until we’re satisfied that it can perform consistently with real-world data. Generative AI models, as advanced as they are, are not perfect. And because deep learning models are designed like black boxes, data scientists cannot explain all the model's decisions.
For example, how do you trust that an AI-powered sales forecasting app accurately predicts product demands? We can’t unless we test the model to ensure that the app meets high-performance standards. Before we deploy the app, we continuously test it for accuracy, explainability, and reliability. Here's the article where we explain the importance of software testing, check it out if you still hesitate if you should outsource software testing.
Step 7: Launch
Once we’re confident that the model is successfully integrated into the app and has met all testing criteria, we release it. As we do so, we brief all critical stakeholders of the changes, specifically the app users. We train operational staff to familiarize themselves with new AI features and provide guidelines for impacted users.
Step 8: Monitor and improvise
AI model’s performance might vary overtime. We continue to observe for cases like biases or inaccurate responses after we launch the app. If we discover such incidences, we apply mitigative measures to improve its performance. Even if the model is performing well, we’ll also need to assess if the model aligns with changing user behavior and evolving technological trends.
Top AI Technologies Used for Business Process Automation
As we mentioned, you’ll need to choose the right AI technology that suits your BPA requirements. These are the common technologies that developers use to automate business processes.
Natural Language Processing (NLP) and Machine learning (ML)
NLP is AI technology that lets software understand languages and converse naturally like humans. It works great for tasks like language translation, sentiment analysis, and summarization. When paired with voice recognition technology, you can use NLP to automate call centers with voice-based conversational chatbots.
Machine learning, on the other hand, allows software algorithms to learn specific patterns and mimic human decision-making processes. Businesses, knowingly or not, have been using different types of machine learning to automate their workflows. Simpler machine learning models, such as decision trees, are helpful in automating repetitive processes with pre-defined rules. Meanwhile, deep learning models like GPT can handle more complex tasks like automated conversations.
Learn how to build conversational AI software that can comprehend and process human language in our guide.
Predictive analytics
Predictive analytics is a subset of machine learning that lets you analyze massive data and make highly accurate predictions. For example, if you want to stock up your restaurants for an upcoming festivity, you can apply predictive analytics. With this technology, you can analyze past data, current trends, price changes, and other events that might affect customer demands. This way, you can avoid overstocking while ensuring enough supplies.
Computer vision
Computer vision is AI technology that can analyze and extract key information from videos and images. When automating business processes, computer vision is helpful for tasks like object recognition, movement tracking and structural analysis. For example, if you own a CNC machining business, computer vision technologies can let you detect minor defects that escape human eyes.
Robotic process automation
Robotic process automation (RPA) automates tasks with software agents called bots. Unlike generative AI, bots follow predefined rules. They are helpful in data entry, order processing, system monitoring, and other repetitive tasks. When integrated with AI, you can use RPA to handle tasks with more significant complexities, such as analyzing social media posts for user sentiments.
How Does Uptech Provide AI Automation for Small Businesses?
Uptech has gone through similar phases that many SMB owners do. We know that you’re constantly seeking ways to innovate your business, but are constrained by time, cost, and talent. Even more so, we’re aware that business owners are keen to leverage the recent boom in generative AI technologies.
Wondering how much AI costs? Check our blog.
Since our founding, we’ve made it a mission to help business owners create purposeful apps for their users. As generative AI emerged, our developers have been actively helping small businesses build AI software to become more competitive.
For example, we built Dyvo.AI, an app that automatically turns selfies into professional headshots. This means that you no longer need to spend on costly studio photography just to get a profile picture for LinkedIn or other professional platforms.
Besides building on our own business-friendly AI solutions, we also help other SMBs automate their workflows with AI. Take Angler AI as an example. The customer growth service provider wants to help their customers improve marketing performance. To do that, we built a platform from scratch that allows business users to predict their campaign results so they can improvise before launching it.
Another example of a business benefiting from Uptech’s AI expertise is Plai. Plai offers performance review services through an online platform. We integrated Plai with AI, which analyzes employee reviews and provides feedback to managers. This reduces the time it takes for managers to create employee development plans.
Future of business process automation
As generative AI evolves rapidly, business process automation as we know it is about to undergo gradual, but definite changes. Whether automating marketing campaigns, or predicting business cashflow, AI will increase the agility, robustness, and security of BPA in various applications.
In this guide, we’ve also seen successful examples of companies in different industries applying AI to automate their business workflows. A more intelligent BPA means companies can improve productivity, reduce costs, and mitigate risks as they grow.
Being AI adopters ourselves, we feel optimistic about what an AI-infused BPA will do for your business.
Talk to our team to explore the full potential of AI business automation.
FAQs
What is AI business process automation?
By definition, BPA automates repetitive tasks based on pre-fixed rules. But AI business process automation takes it several steps further. With AI, BPA software can analyze and interpret complex, unstructured data to help business owners make informed decisions. AI BPA can also self-learn and adapt to changing business requirements.
What technology is used to automate business processes?
There are no hard rules about this. Rather, it depends on the workflow you want to automate. For example, machine learning and NLP are helpful when automating blog creation. Most BPAs use multiple AI technologies, including machine learning, natural language processing (NLP), and computer vision.
Which business processes can be automated using AI?
You can automate most business processes that involve manual or repetitive workflow with AI, such as.
- invoicing
- marketing
- customer support
- logistic
- accounting
And more. That said, AI automation is more impactful for business processes that are repetitive and consume substantial resources. Therefore, before integrating your business processes with AI, it’s best to evaluate your needs to ensure targeted AI automation.
What are the potential challenges of AI business process automation?
When you automate business processes with AI, be prepared for these challenges.
- Data security. To implement AI, you need to train or fine-tune the model with volumes of potentially sensitive data. Without adequate protection, you risk data leakage or breaches, which will affect customer’s trust.
- Ethical concerns. Although generative AI has improved, it might still produce inaccurate or biased responses. Without a guardrail, the model’s inaccuracy will affect the operational decisions the BPA software makes.
- Complexity. SMBs often need help overcoming technical challenges in developing, integrating, and implementing AI to automate business processes. Such efforts require specialized skills like machine learning, data analysis, NLP and computer vision.
How can my business get started with AI business process automation?
Follow these steps to automate your business processes with AI.
- Identify business processes to be automated.
- Choose the right AI model.
- Prepare the training data and train the AI model.
- Integrate your BPA solution with AI.
- Test and evaluate the AI-powered app for performance and security.
- Launch and monitor the app.