Artificial intelligence offers businesses unseen opportunities to boost efficiency and transform workflows. Yet, business owners find it challenging to see the full potential of technology while feeling overwhelmed by the multitude of options available to them. Influenced by hype, they begin making decisions based on flimsy reasoning.
Decision makers should properly assess current performance, set realistic goals, and find practical ways to use AI to truly accelerate business growth. When they leave that out, the results of AI adoption become difficult to measure, leading to missed opportunities and costly errors.
Whether your company leverages AI to improve your in-house processes or builds AI-driven solutions for clients, this article shares what you need to know before starting and proceeding with implementation.
Set Clear Metrics for AI Integration
Think about AI implementation like diving: you need to know the water’s depth to stay safe. When you define specific key metrics for productivity and quality, you gain a clear understanding of where AI can truly meet your needs and expectations.
“It’s much easier to leverage AI if your business has baseline metrics for productivity and quality. Otherwise, the initial excitement might mislead you," says Max Belov. "While AI tools like GitHub Copilot promise a 30% increase in developer productivity, research shows that up to 50% of AI-generated code may still require manual corrections before it’s production-ready.”
Max Belov, Chief Technology Officer at Coherent Solutions
A number of other factors will also impact your final product. That depends on what software you’re building, who your users are, and the scale of your user base. For example, if you’re developing software for 5,000 users versus 50 million, you have to think about bias, compliance, and even hallucinations generated by AI.
Working with a reliable digital engineering partner can provide you with a strategic perspective: you will determine AI uses that will benefit your business the most and develop a solid implementation plan. With that sone, you may start experimenting with AI and gauge its real impact on your business.
Identify Business Applications for AI
Businesses typically apply AI to boost productivity, streamline operations, automate repetitive tasks, enhance customer service, and improve data analysis for better decision-making.
Elevated Customer Experience
AI lets customers quickly find reliable information about products or services through chat interfaces and access customer support 24/7. Solutions like AI-driven virtual try-ons, personalized product recommendations, and lifelike virtual design experiences increase customer purchases.
Increased Employee Productivity
With simple tools like task and communication managers, employees and teams already become more productive. Solutions like AI-powered speech analytics to gather insights from individual chats and customer feedback on products and services truly take off productivity. For example, this helps call center agents give customers with more accurate and personalized responses.
Advanced Biotechnology Development
AI is disrupting the biotechnology field, helping to understand genes and define new therapies based on the gene composition of individuals. It helps pharmaceutical companies comply with GDPR and HIPAA and better control their production processes.
Efficient Manufacturing Processes
One of the biggest challenges for manufacturing companies is finding ways to make their processes better while cutting down on waste. AI helps them catch defects earlier and even predict maintenance issues before they come up.
New Services and Products
AI stimulates businesses to develop new data-driven products and services by analyzing customer behavior. Businesses combine new solutions with personalized marketing content to connect better with customers, increase engagement, and boost sales.
Create Guidelines for Ethical and Responsible AI Use
“Use AI responsibly, not just effectively, in a business context. It should be adopted in a way that aligns with business goals and industry regulatory requirements,” emphasizes Max Belov.
AI requires clear usage policies and risk awareness. Your developers and engineers should understand the associated risks, especially regarding compliance in your particular case. Make sure they receive adequate training.
AI tools should be unbiased and transparent, which hugely depends on training data. For example, in healthcare, biases could lead to misdiagnosing conditions or inappropriate treatment options, raising concerns about patient safety.
Test algorithms thoroughly. This can help you avoid scenarios where legitimate financial transactions might be blocked or sensitive patient data might leak.
Trust in AI models is crucial in business decision-making. However, it might be compromised by AI hallucinations that are common for complex language models and deep learning systems. You should prioritize the explainability of AI models over their accuracy to address model hallucinations. Consider domain-specific model tuning and training, adopt a human-in-the-loop approach, and use feedback loops. For pre-trained models, use self-explanation techniques, asking pre-trained large language models (LLMs) to explain how they arrived at specific results.
The Critical Role of Data in Business AI
Data quality determines how efficiently businesses use AI. Sometimes, having less data is better if this data is relevant, accurate, and secure. Relying on biased or outdated information can mess up decision-making.
Be careful handling historical data: what worked in the past might not be right for today. For example, an AI tool for demand forecasting that was spot-on a few years ago might be a way off if it hasn’t been updated with sales data during big market shifts. Likewise, AI systems assessing credit risk won’t help make solid decisions if they only look at credit histories from before the COVID-19 pandemic.
By enriching your business data, you contribute to better decision-making. Consider internal and external sources of data that can add value to your current sets. As a result, you will gain a complete picture of your business and stay on top of changes in the market.
Make Cultural Shifts in Your Company
You’ve brought AI into your tech processes, but that’s not enough. You need to foster cultural changes within your company to make the most out of AI.
Make sure everyone — from top management to frontline employees — is on the same page about how they use AI. They should cooperate in an environment that promotes creativity and experiments. Whenever new skills are required, provide employees with adequate training while ensuring they use AI ethically and responsibly.
A good way to start is to choose a group of stakeholders who will test AI initiatives first and develop effective plans. When they succeed, scale the outcomes throughout the entire company.
Choose the Right AI Tools for Your Business
There’s a lot of buzz around generative AI like LLMs or image generation tools. But classic machine learning techniques still hold a lot of value. You don’t have to go the extra mile for AI tech stack and can use simpler ML tools for processes optimization, predictions, and pattern recognition.
Algorithms like logistic regression, decision trees, and support vector machines are excellent for predictive analytics tasks. That includes fraud detection, predictive maintenance, and customer churn modeling. They also typically require less data and computing power than the latest deep learning models, which makes them more practical and cost-effective.
When you choose between static or dynamic AI models and human oversight is necessary, make the most optimal decision. Consider your specific need and weigh accordingly the benefits of the flexibility and adaptability of dynamic models against the stability and explainability of static ones.
Transform Your Business with Custom AI Software
Nearly every business today seeks to enhance operations with AI. Its transformative potential helps boost efficiency, make better decisions, and enhance customer experience. Yet, adopting AI solutions is a complex journey. When businesses want to hit their goals faster, they choose an expert provider of digital engineering services who takes a tailored approach to every custom case. With custom AI solutions, businesses build a foundation for long-term growth and see a direct, measurable impact on the bottom line.
