The 10 Latest Artificial Intelligence Trends That Your Business Needs to Embrace
Pohan Lin
Published 07/15/2022
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Artificial Intelligence (AI) has quickly become an essential component for business processes across industries. It’s now more common than not for business tools to make use of AI and machine learning technologies.
According to McKinsey’s The State of AI in 2020 report, more and more businesses are now turning to AI to increase value in their businesses. And 50% of survey respondents report that their companies have adopted AI in at least one business function.
Clearly, AI is big news. So, today, we’re going to be discussing the top ten artificial intelligence trends that will set your business apart.
One of the biggest artificial intelligence trends we’re seeing is the increased use of AI technology for cybersecurity and surveillance. With an increasing amount of business happening online, cybercrime is an increasingly pressing issue for organizations. This is especially true for those with extensive networks of connected devices.
AI techniques are helping to produce more robust security measures in a number of ways. Firstly, AI can learn to recognize and flag criminal activity before it becomes a problem. Secondly, AI can be used to improve access security measures with features like:
Face and voice recognition
Video analysis
Biometric authentication
These are ideal for improving security systems and getting ahead of suspicious activity.
2. AI for Communications
The next trend we’re going to focus on is AI for communications. Next-generation AI tools use Natural Language Processing (or NLP for short) to generate visual, auditory, and text-based data automatically. What’s more, these processes have become so good that AI outputs are virtually indistinguishable from real data.
One of the biggest NLP trends to take root has been the development of AI chatbots. Chatbots can be used to automate business-customer interactions to provide clients with human-like interactions on-demand. This takes the pressure off customer support teams by automating repetitive tasks. And it improves overall access to customer services.
For example, chatbots can easily replace humans to:
Answer simple client questions
Organize appointments
Send out reminders or personalized offers
But as well as real-time communication, AI technology is also capable of creating content. Increasingly, AI tools are being used to generate creative outputs, such as writing headlines or designing logos.
3. Automated Business Processes
More and more organizations now use AI technologies to automate their business processes. That could involve automating your marketing efforts, appointments… the list goes on. AI tools are able to memorize and follow set protocols of tasks. And, as a result, they can help businesses streamline business processes and become more efficient.
Increasingly, manual data procedures are being replaced by automation. Intelligent automation can:
Solve common business challenges
Reduce pressure on employees
Eliminate manual error
Increase productivity and efficiency
The key to achieving a successful digital transformation is scalability.
Marketing automation is taking the business world by storm. With so many business models to choose from in this space, you might be wondering which processes can be automated successfully.
In reality, AI can be applied successfully to both of these marketing models. AI helps affiliate marketers gain valuable insights into the types of content customers enjoy. Automation can also help reduce human-run tasks in a dropshipping business.
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Intelligent Process Automation (IPA) uses Robotic Process Automation (RPA) and AI in combination to automate end-to-end business processes. This is proving to be the key ingredient for successful digital transformations. IPA enables businesses to automate processes aided by machine learning, Natural Language Processing (NLP), and other intelligent automation.
4. Ethical AI
As well as focusing on what AI can do for businesses, there’s a growing awareness surrounding the ethics of AI. And the topic is being discussed more and more at computer science conferences.
Demand for ethical AI is rising. Today’s consumers are increasingly value-driven. And more and more organizations are questioning how we can make use of these technologies in the most ethical way possible.
It’s critically important that we monitor the quality and use of big data because AI technologies use it. AI data compliance (AKA ensuring that all AI systems meet the prerequisite regulatory requirements) is essential to the distribution and use of responsible and ethical AI solutions.
Platforms like Hadoop help organizations manage big data applications. You can learn more in the Hadoop blog post from Databricks.
5. AI for Good
As well as ensuring that AI processes are ethically compliant, there’s a growing call to use artificial intelligence for the global good. To date, AI has been most closely associated with business automation and optimization. But its possibilities extend far beyond this.
Some organizations are starting to think about ways that AI models can be used to help solve pressing global issues and make real societal change. Examples of this include the use of AI technologies for:
Individualized education
Environmental research (e.g., predicting weather events, like hurricanes)
Safer and more efficient care in healthcare settings
6. The No-Code Revolution
One of the biggest barriers stopping businesses from adopting AI-driven processes has been coding. Not every organization has access to professional AI computer science and engineering
leaders with the skills and experience necessary to create automated tools and algorithms.
This is all changing thanks to no-code and low-code tools. You might have already heard of no-code website-building platforms. Perhaps your website was built on one. These types of software are becoming increasingly popular, and it’s all thanks to no-code AI.
No-code AI platforms help companies make use of complex technologies without needing a great deal of technical know-how. They offer a simple interface from which teams can construct AI systems using intuitive drag-and-drop elements and other no-code tools.
No-code platforms allow teams to develop AI models without the requisite experience or cost that was once associated with doing so. That means processes can be developed at low cost, implemented quickly, and used easily (irrespective of technical training).
7. Prioritizing Diversity in AI
Did you know that AI can contribute to biases? Research suggests that a lack of diversity in AI development can contribute to increased racial and gender biases in organizations. Lack of diversity amongst development teams results in products and processes that are biased toward the dominant group.
Unfortunately, this lack of diversity remains common. Research suggests that women only make up 10% of AI researchers at Google and that less than 5% of staff at Facebook, Google, and Microsoft are black.
Prioritizing diversity and inclusion at every stage is the best way to eradicate these biases. So it’s important that AI companies build diverse teams. This is because teams that are diverse in gender, race, age, ability, and cultural background are more likely to be creating and testing mobile apps that reflect the needs of all (rather than just a small selection of) users.
8. AI in the Metaverse
AI is making real strides in the digital metaverse. If you’re unfamiliar with the term, “metaverse” simply refers to virtual environments where users interact. That could be an online workplace, an online game, or any other kind of immersive online experience, like social media.
Metaverse AI is a seriously hot topic right now. The metaverse uses AI technologies to enhance the digital worlds that we interact with on a daily basis. AI is now thought to be one of the biggest contributors to metaverse growth. AI will be the linchpin support for:
Metaverse AIOps
Inclusive user interfaces
Immersive experiences
9. AI for Healthcare
We’re set to see an increased uptake of AI technologies in the healthcare sector. AI has already proven to be a boon to healthcare providers, who can use the technology to facilitate care more
efficiently and allow patients greater access to safe medical care.
AI is making it easier to acquire real-time data from patient health records. This leads to faster diagnosis and care-enhancing processes. Furthermore, AI is effectively assisting hospital staff when it comes to monitoring and managing patient records, hospital admissions, and more.
New, AI-driven technologies like thermal cameras for detecting patient temperatures and contactless delivery tools proved invaluable during the COVID-19 outbreak, and innovations such as these are only set to continue in the sector.
10. AI & IoT
The last artificial intelligence trend we’re going to be discussing today is the relationship between AI and the Internet of Things (IoT). IoT is now commonplace within companies, but many businesses still struggle to use it effectively. The main problem has been how to garner actionable insights from IoT.
By mobilizing IoT products in conjunction with AI, it becomes easy to translate and gather data. More and more industries are starting to combine AI and IoT for better results all around, resulting in what is becoming known as the AIoT.
So, there we have it. You’re all up to date with the ten latest artificial intelligence trends. AI continues to be stable for businesses across all industries, and its use-cases continue to diversify. As your business grows, consider prioritizing these AI developments in your own operations for even better results!
About the Writer
Pohan Lin is the Senior Web Marketing and Localizations Manager at Databricks, a global Data and AI provider connecting the features of data warehouses and data lakes to create lakehouse architecture. With over 18 years of experience in web marketing, online SaaS business, and e-commerce growth. Pohan is passionate about innovation and is dedicated to communicating the significant impact data has in marketing. Check out Pohan’s LinkedIn.
Artificial Intelligence (AI) has quickly become an essential component for business processes across industries. It’s now more common than not for business tools to make use of AI and machine learning technologies.
Pohan Lin is the Senior Web Marketing and Localizations Manager at Databricks, a global Data and AI provider connecting the features of data warehouses and data lakes to create lakehouse architecture. With over 18 years of experience in web marketing, online SaaS business, and e-commerce growth. Pohan is passionate about innovation and is dedicated to communicating the significant impact data has in marketing. Check out Pohan’s 
