Table of contents
System boot. Maximizing AI’s impact on business success
Algorithm activation: Unleashing AI in the wild
Module one. AI in Transportation and Logistics
Module two. AI in Travel and Hospitality
Module three. AI in the Insurance industry and Legal field
Module four. AI in Retail
Module five. AI in Human Resources
Finalization
Initialization
AI has firmly sunk its claws into the business world, and the collective euphoria around it shows no signs of slowing down. According to international research conducted by Stratio BD, 75% of IT decision-makers plan to ramp up their use of GenAI tools in 2025, while 25% intend to integrate GenAI into their core business processes within the next six months.
And why wouldn’t they? AI keeps flexing its muscles with success stories from all sorts of sectors.
We’ve already dipped our toes into ChatGPT-related AI business applications, but today we’re eager to take a leap and explore the vast ocean of AI. Armed with insights from real-world projects, events, and conversations with clients and partners, we’ll show you how AI is reshaping various facets of business processes, all while pinpointing the key factors that fuel peak profitability.
System boot. Maximizing AI’s impact on business success
When we engage with clients eager to leverage AI for business enhancement, a deep understanding of state-of-the-art (SOTA) models is almost never explicitly stated. Does this mean that knowledge of AI tools and the ability to configure them are no longer relevant?
Quite the opposite. They’re foundational, implied rather than spelled out. Because, while crucial, these technical aspects are just one piece of the puzzle for a truly profitable AI implementation. What else matters?
Amplifying a business’s unique strengths
Breaking down business processes in granular detail can work miracles. Or at least tackle complexities and issues with surgical precision. It’s all about identifying the smallest points for optimization, revealing nuanced challenges that might not be immediately apparent, and selectively applying AI to hit the bullseye with precision.
Anticipating potential challenges
Proactively managing obstacles is key to ensuring the resilience of AI in any business. What are the pillars we highlight in this concept?
- Prioritizing legal compliance and data security by consulting legal experts and investing in robust cybersecurity measures.
- Adapting internal policies to facilitate AI integration while ensuring privacy compliance, coupled with comprehensive staff education on AI’s benefits.
- Carefully considering business needs and resources when choosing between open-source and proprietary AI solutions.
- Mitigating the risks of AI hallucinations through strong verification and control mechanisms, including human oversight and rigorous testing.
Ensuring a smooth flow of timely data
Real-time data access is not just a nice-to-have perk — it’s critical, especially in businesses where success hinges on timely insights. That’s why fortifying data foundation with the latest technologies for efficient data collection, secure storage, processing, and insightful analysis using BI tools is an approach that leaves no room for compromise.
Prioritizing ROI
It’s crystal clear: the ultimate objective of any business change is to boost profits in one way or another. However, it often ends up being just that. Therefore, it’s important to view AI integration through the lens of its potential business impact and consistently track this metric as you scale AI within the organization.
Algorithm activation: Unleashing AI in the wild
While AI can certainly deliver business value through small, incremental changes — supporting decisions, automating processes, and tackling specific tasks in any field — more and more forward-thinking businesses are starting to see AI not as a tool for rethinking end-to-end processes and using it on a grand scale.
The exciting part is that AI’s universal charm means it drives such valuable transformations across any industry and environment.
Module one. AI in Transportation and Logistics
You might not drop your coffee hearing about AI in logistics — autopilot technology is practically old news. But here is what gives this concept a fresh spin: an innovative platform — a voice assistant for truck drivers — that transforms decision-making on the go and becomes a highly efficient co-driver that can:
- Cut travel time by 20%
This AI companion understands the roads like a seasoned driver and by optimizing routes and avoiding traffic, it significantly reduces delivery times.
- Reduce incident risks
Safety is paramount. The assistant alerts drivers to potential hazards, helping them make safer choices on the road.
- Reduce unplanned stops by 40%
The system keeps a watchful eye on the vehicle’s health, alerting drivers about maintenance needs before they become full-blown breakdowns.
- Save 10% on energy
With optimized driving modes and energy management, this technology helps reduce fuel costs.
The brilliance of this example of AI in logistics also lies in the fact that it’s deeply integrated into the company’s business operations:
- Syncing with onboard computers
The platform synchronizes with the truck’s onboard systems, providing real-time data about the vehicle’s condition and route.
- Connection with order management
The voice assistant offers instant access to current and upcoming orders, enabling drivers to plan their actions efficiently.
- Multilingual real-time translation
Catering to an international fleet becomes effortless as the system supports multiple languages, translating on the fly to prevent misunderstandings.
- Truck management instructions
Equipped with an extensive database of truck management instructions, the platform assists drivers in troubleshooting and resolving issues promptly, thereby maintaining operational continuity.
Such a marriage of advanced AI with traditional logistics promises to drive unprecedented growth and sustainability and is paving the way for smarter, safer, and more efficient transportation.
Module two. AI in Travel and Hospitality
Imagine planning a trip and being able to delegate every single detail to an app. You don’t need to phrase your requests in any special way for the machine to understand you. Just talk naturally, and the program guarantees to provide you with accurate, reliable, and relevant information, as if a human were assisting you.
That’s almost an exact description of a recently developed tourist guide that promises precise, factual information delivered through a user-friendly interface.
But how was it pulled off, especially given the current challenge of making LLMs deliver data without hallucinations (the issue that primarily arises due to the absence of specific metrics to measure these hallucinations, making subtle inaccuracies much harder to identify and measure than obvious errors)?
The company that decided to leverage AI in the travel industry and created this app has trained their LLM to generate structured database queries. Instead of just asking the LLM for facts about a location, they instruct it to create a query based on the user’s input. This query is then sent to a structured database, ensuring the information retrieved is accurate. Finally, the correct data is presented to the user in an easy-to-understand format.
Crush your business goals faster with AI
Do you need more methods and tools for refining the relevance of AI answers and protecting your business and clients from AI hallucinations?
Module three. AI in the Insurance industry and Legal field
Many companies face the challenge of managing large volumes of unstructured data: receipts, contracts, patents, you name it. They’re working hard to scan, digitize, and organize it into a readable and accessible format for efficient searching. AI has become quite proficient in this arena, widely employed to streamline these processes across various industries.
However, there’s also a higher level of AI application, which is attracting significant investment from insurance and legal companies — AI contract drafting and risk assessment.
Contract drafting
The use cases of leveraging AI in insurance and other legal spheres of business today extend beyond AI learning to draft accurate and clear documents that cover all of a company’s legal bases. AI systems are also getting handy at semi-automatically communicating with counterparties, e.g., they can receive a contract with amendments, analyze it, and, based on predefined parameters, either accept the changes, reject them, or suggest alternatives within the permissible risk parameters. This process requires high data accuracy, as the system must make final decisions based on the company’s knowledge base.
Document summarization and accessibility
Another relevant issue that AI is great at solving is the understanding of lengthy instructions and license agreements, which are often complex for the average person. This is particularly important when choosing among several products, where each novel-length agreement or instruction may be laden with intricate legal and technical jargon. So, leveraging AI to distill clear and succinct summaries from these texts greatly simplifies decision-making processes.
Module four. AI in Retail
eCommerce retailers are now integrating Generative AI into their customer support and product recommendation systems, enhancing the shopping experience by making AI act as support agents and product advisors.
One of such AI-in-eCommerce examples looks the following way: imagine you notice a tiny scratch on your car. Instead of diving into the murky waters of online forums or dialing up a grumpy mechanic, you ping a cheerful AI chatbot. You can upload a photo or describe your issue and receive instant personalized advice, not only with the exact product needed but also with step-by-step instructions on its effective use.
The retailers are taking such AI use cases in eCommerce further by integrating Quality Assurance functionalities into the chatbot, which asks probing questions on various topics related to the customer’s interaction and gathers feedback to continuously improve the service. This iterative improvement process ensures that the AI-driven support remains accurate, helpful, and responsive to customer needs.
Module five. AI in Human Resources
Generative AI in HR offers a fertile ground that begins with automating routine processes and culminates in pinpointing the right candidate with nearly no manual involvement, up until the final stage of the interview. Leveraging a robust HR platform can complement AI tools, providing a comprehensive solution for managing recruitment, employee engagement, and performance tracking within a single, integrated system.
AI algorithms can sift through mountains of resumes and cover letters with the precision of a seasoned recruiter, pinpointing top candidates while mitigating bias in hiring processes and focusing on qualifications rather than personal data. This not only streamlines the initial screening process but also ensures that HR professionals can focus on forging deeper connections with potential hires.
Beyond recruitment, AI-powered systems are revolutionizing how feedback is collected and analyzed. By anonymizing responses and crunching data at lightning speed, these systems unveil invaluable insights into employee satisfaction and engagement levels, empowering organizations to foster a more supportive and productive work environment.
Moreover, Generative AI for HR isn’t just transforming the hiring process — it’s used to analyze employee data to predict turnover, identify skills gaps, and assist in creating targeted training and succession plans to help HR prepare the workforce for future business needs.
Finalization
So, you’ve got a promising pocketful of ideas for implementing AI in your business. What comes next? In case you’re ready to add your own AI use case to this list, you couldn’t think of a better time than now. We’d be happy to lend our expertise, insights, and hands-on assistance any step of the way.
Alternatively, if you’re intrigued by this technology and willing to see how it can amplify your business’s value, our experts are ready to ideate and unlock AI’s potential tailored precisely to your unique context, as AI’s versatility spans far and wide: from optimizing marketing spends through precise targeting and deploying LLM-driven Telegram bots for ad campaign management to improving fraud detection or risk assessment in Finance and revolutionizing Healthcare diagnostics and even accelerating drug discovery.
The sky’s the limit, so how about making AI the fuel to propel you there?
