Whether an entrepreneur or a senior business leader in an enterprise, if you are in business then you are likely studying technology innovations keenly. You constantly evaluate how technology innovation might change your business.
Artificial Intelligence (AI) is one such technology that could transform your business. To understand its potential though, you ought to read this guide explaining the 5 ways AI will change your business in the near future.
Why does AI matter?
AI is a technology with significant potential, as I have explained in “How much does it cost to develop an AI solution for your company?”. This technology involves “training” computer systems so that they can “learn” from experience.
This requires a massive amount of data. The said computer system adjusts to new data inputs and carries out its tasks better as more data is available to train it. You can read “Artificial intelligence (AI)” to understand this better.
Many industry verticals have key AI uses, e.g., financial services, automotive, insurance, healthcare, logistics, healthcare, transportation, oil & gas, etc. Consequently, there is a growing market for this technology.
Forbes quotes Gartner to state that AI will create $3.9 trillion business value in 2022. This Forbes report also quotes IDC, and it states that the market for AI will be worth $77.6 billion in 2022.
How AI can change your business
Let’s now understand 5 ways in which AI can change your business, which is as follows:
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1. Transform customer service
Businesses have no relevance without customers, therefore, customer service is a key function for every business. Customers are increasingly demanding better services, moreover, businesses face cost pressure. It’s not easy to provide great customer service, however, AI can help.
Challenges facing customer service teams:
Customer service teams face numerous challenges, e.g.:
- Insufficient knowledge base;
- Call/ticket routing issues;
- Communication challenges;
- Highly demanding customers;
- Failure to set expectations;
- Too many tickets;
- Slow resolution time.
You can read more about these in “12 biggest customer service challenges and how to solve them”.
How AI can help to improve customer service
AI can address many of the above-mentioned challenges. It can help to improve customer service in the following ways:
- Businesses that deploy AI can understand how their customers feel at an individual level about their products and services, moreover, such businesses also get an aggregate view. They gain a better understanding of their customer base.
- Skilled and trained customer service representatives are becoming more expensive, therefore, businesses must use them where their skills can add value to customers. AI bots can handle easier customer queries.
- Since AI bots work 24/7, customers get immediate answers to many of their questions.
- With the AI bots resolving easier questions, the waiting time for customers requiring experienced customer support representatives reduces.
- As AI has advanced language translation capabilities, businesses that deploy AI can improve their communication with customers across the world.
You can read more about this in “3 ways AI can help businesses improve customer relations”.
Usage of AI in customer service
Several reports are highlighting the significant potential AI has in customer service, e.g.:
- Gartner has predicted that by 2020, 85% of customer interactions will happen without the intervention of a human customer service representative. AI will play a big part in this transformation, and you can read about this in “What you need to know about the rise of AI in customer service”.
- Salesforce believes that AI will make a substantive positive impact on customer service. The technology giant cites the example of H&M, the clothing retailer already using AI successfully in their customer service. Read “Rise of the chatbots: how AI changed customer service” to learn more about this.
2. Prevent frauds with the help of AI
Businesses must retain their customers by building trust. Building trust can take decades, however, one fraudulent transaction can erode that trust in a matter of days!
Banks, financial services institutions, eCommerce companies, and many other businesses face the risk of customer churn due to fraudulent transactions. Preventing fraudulent transactions can be hard, however, AI can help noticeably.
Why is it hard to prevent fraudulent transactions?
Many challenges make it hard to prevent fraudulent transactions, e.g.:
- Cybercriminals are constantly upgrading their capabilities, therefore, it’s always an uphill battle for businesses.
- When business gain success in preventing one type of fraudulent transactions, newer threats emerge within no time! E.g., the success in combating payment frauds were soon followed by “Account Take Over” (ATO) frauds, as you can read here.
- Web and mobile applications often have crucial application security vulnerabilities, e.g., injection, cross-site scripting (XSS), etc. These make the job of cyber-attackers easier, according to the Open Web Application Security Project (OWASP) top 10 application security risks – 2017 report.
How does AI make a difference?
AI can significantly boost fraud-prevention efforts in the following ways:
- Businesses can use deep learning models to detect new fraud patterns.
- Admittedly, cyber-criminals are nimble and they are always creating new tactics to execute fraudulent transactions. It could be hard to frequently update deep learning models, however, using Ensemble models can help. Ensemble modeling uses multiple models for a single task, therefore, they are better at detecting frauds.
- Businesses can use AI to classify transaction patterns as suspicious. It’s complex to get this right since only a small percentage of customers try to defraud a business. If the business identifies too broad a set of transactions as suspicious, then it could result in degraded customer experience. The key is to continuously study the patterns and refine them.
- Enterprises should focus on building explainable AI models so that the AI-powered fraud prevention system clearly states why a transaction is declined.
Read more about this in “4 major challenges facing fraud detection; ways to resolve them using machine learning”.
Using AI to prevent frauds
There are numerous examples of AI at work to prevent frauds. One such example is Danske Bank using AI, in a partnership with Teradata. Danske Bank has increased detection of real fraud by 50%, as a result of using AI. Read more about this in “AI-based fraud detection in banking – current applications and trends”.
3. Secure your IT infrastructure with the help of AI
IT assets are very important for businesses, however, they are vulnerable to security risks. AI can help businesses to secure their IT infrastructure and assets.
Security challenges facing enterprise IT infrastructure and assets
Businesses need to contend with several challenges while securing their IT infrastructure and assets, e.g.:
- Cyber-attacks continue to grow, both in volume and sophistication.
- Many businesses use both on-premises and cloud infrastructure, moreover, they also engage service providers. This exposes their sensitive information to high risks.
- There are many unused, unidentified, and inactive devices that cyber-attackers can exploit to attack the IT assets of an enterprise.
- Open-source software and 3rd party applications can expose an enterprise to IT security risks.
- IT security processes are often manual, therefore, it’s hard to meet stringent regulatory requirements. When a business fails to comply with such standards, they might be subject to penalties.
- Enterprises often find that their IT security processes are unable to keep up with the break-neck pace of technology innovations.
- Many businesses have sensitive information stored in silos, and sub-optimal IT security processes can’t adequately protect them.
Read more about these challenges in “9 pressing IT security challenges – and how to mitigate them”.
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How AI can help businesses secure their IT infrastructure and assets
Artificial Intelligence can enhance the security of IT infrastructure and assets in several ways, e.g.:
- AI-powered event monitoring solutions can recognize patterns in web requests, which can help in detecting cyber-attackers.
- Enterprises can scan a large amount of data over the Internet using AI-powered information security solutions, and learn how cyber-attacks are originating. These systems can then recommend solutions. Read more about this in “Is AI fundamental to the future of cybersecurity?”.
- AI can help you to improve your response time for cybersecurity incidents.
- Since AI-powered cyber-security solutions can manage a large set of alerts and incidents, cybersecurity experts can get the time to focus on important threats. Read more about this in “Why artificial intelligence in cyber security is need of the hour”.
An example of AI-powered applications in cybersecurity
ForAllSecure, an American start-up has created an AI-powered cybersecurity bot, named “Automatic Exploit Generation” (AEG). AEG can find bugs in commercial off-the-shelf (COTS) as well as enterprise application software.
It can identify whether the bug can be exploited. AEG won the 2016 Cyber Grand Challenge, which was organized by The Defense Advanced Research Project Agency (DARPA). Read more about this in “Artificial intelligence and security: current applications and tomorrow’s potentials”.
4. Transform your supply chain management with AI
Supply chain management is one of the most complex operations in any business, and AI can help to transform this.
Supply chain management challenges
A complex function, supply chain management faces several challenges, e.g.:
- Customer demands are more volatile and complex, and they are increasingly expecting better services.
- Costs for supply chain management are rising, and this is amidst growing competition.
- Attracting the right talent and retaining the top performers have become harder.
- Regulatory requirements are evolving, and they are often stringent.
Factors like geopolitical instability, environmental concerns, and a complex supplier landscape add to these challenges. You can read more about these in “The challenges ahead for supply chains: McKinsey Global survey results”.
How does AI help with supply chain management?
There are various ways in which AI can improve supply chain management, e.g.:
- AI can offer contextual intelligence, and this can help a supply chain management team to manage the inventory better. This reduces operating costs.
- Businesses using AI in their supply chain can analyze the performance of their supply chain management operations, which helps them to improve their efficiency.
- Demand forecasting improves with AI since this technology can help to analyze a large volume of data.
- Supplier selection can improve with AI.
- You can improve your supply chain management-related decision making with the help of AI.
Read more about these advantages of an AI-powered supply chain management system in “How AI is revolutionizing global logistics and supply chain management”.
An example of an AI-powered supply chain management solution
LLamasoft, an American company founded in 2003 has a supply chain planning and design software, and it’s powered by Machine Learning (ML). Demand Guru, i.e., its predictive demand modeling software uses ML to identify hidden patterns in historical demand data, and this helps businesses to optimize their supply chain management.
Schneider has used the expertise of LLamasoft to improve its supply chain management. You can read more about this in “Artificial intelligence in supply chain management – current possibilities and applications”.
5. Improve your recruitment with the power of AI
People make a company great, therefore, recruitment is a very important function in your business. Businesses are finding it hard to recruit the right talent, and AI can help them.
Challenges facing the recruiters
Recruiters face several challenges, e.g.:
- It’s hard to attract the right talent in a highly competitive job market.
- There is a significant lack of communication between recruiters and hiring managers.
- Businesses lack the required analytics capabilities to make the right recruitment decisions.
- Recruiters must hire high-quality human resources at speed and scale, and achieving this balance is hard.
- Sub-optimal recruitment processes result in wasting valuable time.
Read more about these challenges in “7 biggest recruitment challenges faced by modern recruiters”.
How businesses can improve their recruitment processes with AI
AI can improve the recruitment processes in several ways, e.g.:
- AI-powered recruitment solutions can analyze and shortlist resumes.
- Analyzing social media and similar sources to build a candidate profile is easier with AI.
- Employing chatbots to interact with applicants can expedite the recruitment process. An example of such a recruitment-focused conversational AI platform is mya.
- AI-powered recruitment solutions can collect information from voice and text messages, moreover, they can analyze the vocal tone and body language of the applicant.
Read more about this in “How AI is transforming HR with more sophisticated, less biased recruiting”.
Planning to transform your business with AI?
AI has a significant potential to transform your business, however, developing such AI solutions can be hard. AI skills are niche, and such development projects are complex.
Consider engaging a reputed software development company for such projects. Our guide “How to find the best software development company?” can help you to find one.
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