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AI is not new. In fact, it was invented in the 1950s but has only recently become widely accepted in modern business.
Despite this, the AI industry moves in waves and trends just as fast as any other. This makes it crucial that a business stays up to date on what’s working and what isn’t. Doing so can give a company a competitive advantage while improving marketing and advertising performance.
With that being said, today I will be sharing emerging trends in the AI industry that you need to be aware of moving into 2020.
1. Predictive Analytics
You don’t need a crystal ball to know the future. You just need predictive analytics, which uses a combination of machine learning, historical data and other processes to predict future outcomes. Using predictive analytics, a company can take advantage of patterns and trends to improve everything from its advertising to security.
Not only is it becoming more widely used, but it is also helping businesses increase their bottom line while gaining an advantage over competitors, thanks to:
• A lower barrier to entry with easy-to-use and affordable platforms.
• Increased amounts of data and analytics available from tools and other channels.
• More market saturation forcing companies to find a way to differentiate.
Moreover, the predictive analytics market is forecasted to hit $10.95 billion by 2022. It has experienced 21% compound growth since 2016 and appears to be trending in that direction, making it a lucrative AI trend worth keeping on your radar.
2. Higher Use Of Anomaly Detection
Budgets getting missed, integrations breaking, and features forgetting to be turned on are a few of the daily woes an agency faces. These are all human mistakes, and completely normal, too. However, they can have a high cost.
That’s why anomaly detection is becoming more widely accepted by organizations to find problems before they happen. This AI-driven procedure compares current and historical data to find datasets that stand out. These can be isolated to discover flaws in cybersecurity, marketing, advertising and any area of business.
Not all is grim, however. Anomaly detection is also capable of uncovering advantageous opportunities for business. This can be anything from finding the most profitable PPC creatives to SEO keywords or customer segments. Ultimately, it allows agencies to focus on what humans do best while AI takes care of optimizations in the background.
3. Machine Learning-Driven Cybersecurity
Cybersecurity is a growing concern globally. Losing customer or proprietary data is the last thing you want for your business. In fact, 67% of small businesses experienced cyberattacks in 2018. That’s why we are seeing an increase in cybersecurity driven by machine learning models.
These tools use AI that continually runs in the background as a business operates, spotting threats before they cause damage. It enables an organization to run smoothly while having peace of mind that they’re protected.
Microsoft’s Windows Defender Advanced Threat Protection, or ATP for short, is a prime example. This software, built into Windows 10 devices, deploys cloud AI and machine learning algorithms to detect threats and misconfigurations that can cause harm.
4. More User-Friendly AI Platforms With Increased Adoption
AI can seem intimidating. It’s complex and newer technology, making it more difficult and slower to be adopted by agencies. However, things are changing: According to a Gartner survey, 37% of businesses surveyed have implemented AI in their company as of this year, and this number is rising.
This is thanks to more user-friendly AI software being released, which focuses on adoptability and presenting data in a noncomplex fashion. Users of these tools don’t have to be experts with machine learning and AI to integrate them with campaigns and easily read the data outputs. Along with simple interfaces and straightforward dashboards, more agencies are able to reap the benefits of artificial intelligence without feeling intimidated.
5. AI For Productivity And Work Balance
When you think of AI, it’s easy to think of data, machines and algorithms. Yet, we’re starting to see an increase in AI technology being used to improve the human element of a business.
AI, as discussed with anomaly detection and cybersecurity trends, is capable of processing tasks in the background as an organization operates. This allows the computers to do what they do best — processing, optimizing, etc. — while the people running a business tend to their talented areas. Remember, AI isn’t made to replace an operator, founder or VP of marketing, per se. Rather, it’s best suited to quietly conduct computer-related activities faster than we can.
PwC estimates AI will contribute $15.7 trillion to the global economy by 2030. It predicts that most of this increase will be a result of stimulating consumer behavior, enhancing products and improving labor productivity.
The company VMware is an excellent example of AI improving work balance. According to this case study, as it began to scale its operations, VMware struggled to meet targets and quality standards.
The company opted to integrate an AI-driven content solution, which automated basic tasks like editing and corrections. With over 100 writers and several editors, these small tasks were piling up and getting in the way of high-grade activities.
The saved time from the AI solution was spent on training more writers, onboarding new members and creating better systems.
Final Thoughts
AI is a game-changer. Despite it being many decades old, it’s only recently been globally adopted by a wide range of businesses and industries. Identifying and capitalizing on AI trends can keep your company one step ahead of competitors while achieving a higher level of productivity.
One of the first trends to consider leveraging is predictive analytics. Through big data and machine learning, this is helping companies forecast better solutions and decisions. Similarly, anomaly detection is being utilized to find opportunities and weak points in an organization to thrive and protect assets. Cybersecurity is also taking an AI approach with machine learning to get smarter at detecting threats.
As AI becomes more adopted, we’re seeing case studies and examples of how it enhances not only complex operations like these, but the day-to-day human side of running a business, too.
