AI In Business Examples
Artificial intelligence has been democratized with ChatGPT, and businesses started adopting it to routinely solve problems. And to great effect.
From revolutionizing customer interaction to streamlining operations, AI’s influence is exponential and goes beyond self-driving technology with its autonomous vehicles or robots.
AI in business examples: 6 Use cases
4 in 5 businesses rank artificial intelligence as a top priority in their business processes, according to a Forbes study, which comes as no surprise.
Artificial intelligence in business implies AI systems that spot patterns very rapidly when given access to data sets and automate a big chunk of work with its generative AI algorithms.
Do not worry, as deep learning algorithms are so evolved that they don’t need access to complex or big data sets. They’re effective even on a modest amount of data collected.
1. Artificial intelligence in time management
AI revolutionizes time management by automating time-tracking tasks, offering insights into how we approach our workloads, and giving us personal, personalized insights.
Besides revealing work patterns, it helps in adopting optimal task allocation and understanding processes that need optimization as they’re time-wasters.
A thorough time tracking and management process with artificial intelligence aids businesses to increase profitability by decreasing the level of over-serving customers, too.
Examples of artificial intelligence in time management:
Bang&Olufsen’s IT team increased productivity and saved 10 hours a week by tracking time with an AI-powered time-tracking tool. They understood where their time was going without making efforts to edit manual timesheets, which, in turn, helped the team have a more efficient task and time prioritization.
Beilquadrat, a communications agency, increased project revenue by 25% with AI time management apps. It also allowed the team to accurately track more of their work time and objectively bill up to 25% more time on different projects.
Envision Design, an IT consultancy, became 20% more profitable after the team started tracking time with artificial intelligence. The team developed a better time management relationship and was able to charge accurately for every service.
By analyzing past trends and current progress with AI systems, businesses can make strategic moves with more confidence and remove the guesswork of massive amounts of data. This leads to overall better business management.
Timeular
Timeular is one of the best AI tools for productivity, and it includes leave management features, too.
This AI powered time tracking tool that also works as a productivity tracker promises to automatically do all-time-tracking operations for you while you dedicate only one minute a day to it.
Det er anerkjent for å gjøre tidsregistrering enklere ved å bli kåret til "Best Ease of Use Tool in 2023" av Capterra, og det samme gjelder kundene:
Kaitlin Snow Seamons, kreativ direktør i Harmon Brothers
Here are examples of how Timeular helps in business:
Enhances personal productivity with an AI-generated productivity dashboard – helps you understand at an individual level what blocks your productivity and how to improve it. The AI captures the most used apps, tools that make you procrastinate, and times when you are most productive or unproductive. All data is tracked automatically for you, with 100% privacy – only you can access this dashboard.
The AI-powered time tracker adds suggested time entries to your calendar automatically, so you have an accurate time capture, an objective overview of time spent on work, and accurate timesheets for client reporting or billing. Your automated time capture is generated based on your calendar events and past calendar entries.
Other ways Timeular contributes to your business:
Offers a physical time-tracking gadget that helps track time faster, easier, and with enjoyment, which leads to more accurate time tracking;
- Generates automated easy-to-digest time reports that aid in understanding how your team spends time, what activities are most prolific compared to their profitability, and makes client reporting seamless;
Helps you stay on a time budget with budget notifications and alerts so that you don’t go over the budgeted amount of time you awarded to a project or task and stay profitable;
If you need billable hours tracking, you can monitor and track billable time in one click.
- It provides overtime tracking and PTO tracking.
TIP: Timeular is an excellent time-tracking software for marketing agencies.
Si farvel til usammenhengende AI-verktøy for tids- og permisjonshåndtering. TimeularMed AI-forslag til tidsregistrering, automatisert sporing og smart produktivitetsinnsikt i én og samme app.
2. Artificial intelligence in customer support and service
Artificial intelligence is not just a back-office phenomenon. One of the first business functions that has been revolutionized by implementing AI is customer service.
The all-time complaints, such as long hold times or hard-to-find information, can be easily solved by AI-powered chatbots and virtual assistants. Based on a cognitive computing engine that mimics human-like arguments, AI chatbots can extensively offer personalized touchpoints that drive customer engagement.
Examples of artificial intelligence in customer support and service:
Lemonade, an insurance company, uses AI chatbots to address new customer queries – its AI agents, Jim and Maya, are powered by machine learning algorithms. The AI smart assistants can analyze customer conversations, understand customer requests, and correlate data points to generate an insurance premium price.
Meta has integrated AI into their customer support infrastructure, too, recognizing the potential for AI to not only provide a quick and reliable service but also to significantly reduce operational costs.
TIP: Dive into our article about the best AI tools to add to your stack, where I’ve expanded on the features of Kustomer, an AI tool that enhances customer service.
While it may seem threatening for customer-serving teams, chatbots and virtual assistants can indeed become the first line of customer relations, offering immediate, round-the-clock support.
On the flip side, human employees can escape the burden of redundant work, sometimes part of this business function. They can focus on process automation needs for scaling the impact, increasing SLA times on more complex matters, or performing quality control on AI agents’ performance.
3. Artificial intelligence in marketing
Much like AI in customer service aids in better customer relationship management, marketing teams are embracing artificial intelligence to engage and predict buying and customer behavior with more precision.
In essence, artificial intelligence enables marketers to engage customers with tailored messages at the right time and through the right channel. However, AI already covers all key functions of marketing.
From personalized product recommendations to optimized email marketing campaigns to content creation and curation, artificial intelligence is automating most functions.
To ensure that every interaction is meaningful and fosters brand loyalty, features like lookalike audiences, dynamic ad optimizations, or sentiment analysis are part of the marketer’s AI toolkit.
Anbefalt lesning:
- Business productivity reinvented: Ways to stay ahead of your competition.
Examples of artificial intelligence marketing:
The popular Google Ads and Facebook Ads use AI to target specific demographics, analyze keywords, and predict customer actions, ensuring maximizing marketing spending for the highest return on investment.
The giants Amazon and Netflix use AI for predictive analytics to generate personalized recommendations based on the customer’s history. Amazon uses AI algorithms to assist the online shopping experience of customers based on past purchases and personal preferences, while Netflix suggests to users what to watch next.
All in all, artificial intelligence applied in marketing improves ad targeting and introduces predictive and adaptive capabilities that would otherwise require massive amounts of data analysis.
- Check out the best AI tools for marketers to discover 11 effective marketing tools that can be added to your toolkit.
4. Artificial intelligence in sales
Both sales and marketing teams are leveraging AI recommendation engines to deliver a personalized touch that resonates with consumers. However, the sales teams seem to have been the early adopters of ChatGPT.
Artificial intelligence in business can massively increase a company’s turnover and boost sales opportunities.
A McKinsey & Company study revealed that there is a clear link between a company’s AI maturity and revenue growth:
“Organizations that report faster growth in revenue over the past three years were also more likely to be further ahead when it comes to AI maturity. AI is perceived as a long-term strategic priority for innovation, with 76 percent of the respondents citing AI as fundamental to the success of their organization’s strategy”
Examples of artificial intelligence in sales:
Amazon masters the art of automated upsells and cross-sells with its AI-powered recommendation system. Similar capabilities are available for your sales reps to recommend services or products based on what past buyers have been keen on.
Sales leaders can navigate through customer data and buying intent at a glance. They can check an automated report that includes all signals in sales reps’ phone calls and make a forecast of future incoming deals. Gong.io is a tool that helps businesses with similar matters.
Machine learning algorithms can analyze sales data in CRM systems to identify patterns that aid in refining lead qualification and prioritizing high-value prospects, which helps in lead scoring and prioritization.
Sales opportunities can increase massively due to AI’s ability to mine in-depth customer data and free up time for strategic thinking.
5. Artificial intelligence in hiring
Though AI has permeated the human resources function at a slower pace, it is becoming more and more visible.
AI in recruiting is not about replacing human decision-makers but empowering them to make more informed and fair choices while streamlining candidate selection.
Recruiters use predictive analytics to sort through candidates faster and analyze resumes, social media profiles, and other online sources, aiding in pre-screening.
A great effect of artificial intelligence in hiring is that it reduces unconscious biases that can creep into recruitment decisions. By analyzing resumes and applications without preconceptions or assumptions, AI algorithms deliver a more equitable assessment of potential employees’ competencies.
Hiring artificial intelligence in business examples:
LinkedIn has used artificial intelligence in business processes for years, such as algorithms aiding recruiters in writing job descriptions, matching job seekers with relevant opportunities, or aiding professionals connect with peers with similar interests.
Amazon went even further by developing its tool for hiring with AI, called Automated Applicant Evaluation. This tool assesses applicants for job openings by comparing their resumes with current workers in that same role.
The efficiency of AI comes from its capability to quickly process vast amounts of data, identifying the best-fitted candidates for a position based on predetermined criteria, along with perks such as removing biases.
6. Artificial intelligence in cybersecurity
The more businesses get digitized across multiple industries, the more substantial the role of security becomes, as threats are scaling and becoming more complex.
AI-powered cybersecurity solutions leverage AI for pattern recognition and anomaly detection out of massive amounts of unstructured data to protect sensitive data from cyber-attacks and breaches.
Cybersecurity artificial intelligence in business examples:
Apple can be called the pioneer of AI security products, and its machine learning models identify potential vulnerabilities before being exploited.
The eventual goal of AI cybersecurity is creating an autonomous security system that can not only react to threats but anticipate them.
AI tools examples
Find more examples of AI tools for business in our separate blog article.
Kustomer
Kustomer helps you with all-time customer service complaints as a unified system for managing customer support and interactions. It streamlines customer experience and interactions, automates your FAQs and chatbot replies, and provides service 24/7.
Examples of how Kustomer helps in business:
Translates automatically in 70+ languages and replies through the bot or transfers the chat to a native speaker, according to a quick analysis;
This AI agent deploys bots across various platforms like email, chat, and social media to automate all routine tasks;
Detects user behavior and the tone of the customer and offers personalized suggestions to its interlocutors while also automatically anticipating wait time;
Its replies are based on historical customer data;
Textio
Textio is the app that helps you remove the hitting unconscious biases and align more with diversity and inclusion as one of your values across the hiring process. Textio’s focus is primarily on enhancing recruitment, removing hiring biases, and guiding performance review processes, too.
Examples of how Textio helps in business:
Helps managers automate the performance feedback writing process in an unbiased and actionable way;
Adds real-time automatic suggestions on the diversity of your hiring pipeline will be based on what a hiring manager writes in their job descriptions;
Explains how a job post appeals to different groups through bias interruption;
LogRhythm
LogRhythm focuses on delivering AI cybersecurity solutions to detect threats and anomalies.
Examples of how LogRhythm helps in business:
Detects threats automatically, which aids in minimizing detection time.
Automates incident response time to neutralize threats quickly;
It has self-evolving AI, one of the most convenient features of LogRhythm, as it continuously improves its capability to detect threats and analyze them to stay ahead of cyber threats.
Offers customized security solutions for multiple industries like healthcare, financial services, and utilities, addressing unique industry needs.
Konklusjon
Adopting artificial intelligence (AI) in business is becoming necessary, not just a trend. From improving operational efficiency to enhancing customer service and supporting cybersecurity, AI tools like Timeular, LogRhythm, Kustomer, and Textio are pivotal in transforming businesses. Their ability to automate tasks, provide insights, and personalize experiences offers businesses a significant competitive advantage.
Du er kanskje interessert i:
- Hva er automatisering på arbeidsplassen?
- De beste verktøyene for små bedrifter i 2024
- Hva er de beste produktivitetsverktøyene?
- Topprangerte verktøy for prioritering av arbeid
- What are the best AI tools for small businesses?
- 10 Best Prioritization Techniques in 2024
VANLIGE SPØRSMÅL
What is natural language processing (NLP), and what is its impact?
Natural Language Processing (NLP) is an AI branch focused on making computers comprehend and generate human language and human-like arguments. It is widely used in business functions such as customer service for chatbots, content analysis for sentiment detection, and language translation apps, significantly enhancing communication and data processing capabilities.
How does AI enhance fraud detection?
AI boosts fraud detection by utilizing deep learning to analyze transactions and identify anomalies, signaling potential fraud. It also engages facial recognition technology to verify identities, adding a critical layer of security against impersonation and fraudulent activities. Therefore, it significantly strengthens fraud prevention efforts. Banks, for example, have already implemented artificial intelligence to detect suspicious transactions.
How does AI contribute to predictive maintenance?
Predictive maintenance is primarily used by businesses that own equipment or machinery, and it forecasts potential faults before they result in downtime. Predictive maintenance is essential as it transforms maintenance workflows from reactive to predictive and proactive, preventing equipment from prematurely breaking down.