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From educational and business leaders to advertising agencies and creators, everyone is talking about AI—and their thoughts and feelings run the gamut. While some may fear that this new tech heralds the end of original thinking, others are convinced that AI is the long-sought-after solution for performance-based tasks of the day. So, is AI a threat to critical thought, or is it the holy grail for businesses everywhere? Our AI blog series will cover its involvement in business optimization, writing, and design to help you explore the latest use cases while considering the benefits and drawbacks of using AI in your business. 

So let’s dive in and take a closer look at all things AI and business. 

According to McKinsey’s“The state of AI in 2021” survey, 56% of all respondents report AI adoption in at least one business function, up from 50% in 2020, while Accenture’s report on AI found that 84% of C-suite executives view it as support in achieving their growth objectives. AI tech is moving well past the experimental phase and into a core part of many businesses operations. Although there are seemingly countless ways AI can be used, most applications focus on driving growth with benefits that include:

• Boosting efficiency through process automation 

• Improving the speed or consistency of customer service 

• Using customer insights to inform decision-making 

• Uncovering opportunities for new products and services

Let’s face it, businesses LOVE data because it makes the messy work of creating feel safe and purposeful while at the same time grounding the intangible into cold, hard facts. So it should come as no surprise that these massive repositories and data sets generated in seconds are attractive to businesses worldwide. With the help of AI, companies can now capture user data to help make more informed business decisions and access more relevant data than ever before. According to Forbes, the amount of data created and consumed increased by 5000% between 2010 and 2020. 

How are businesses using AI to keep up? Let us count the ways.

Predictive Analytics: AI algorithms can be trained on historical business data to predict future trends and outcomes. For example, a company might use predictive analytics to forecast sales or customer churn and be able to make smarter decisions faster.

Natural Language Processing (NLP): NLP can be used to analyze unstructured data, such as customer feedback or social media posts. NLP algorithms can identify patterns and sentiment in this data, helping to guide business decisions based on audience opinion. Insights gained from this analysis can then enable companies to identify opportunities for improvement and build on areas of strength.

Process Automation: AI has the power to automate routine tasks such as data entry and processing, freeing up employees to focus on higher-level tasks.

Supply Chain Optimization: AI can optimize supply chain operations by analyzing data on inventory levels, production capacity, and shipping times to identify opportunities for efficiency improvements.

Variational Autoencoders (VAEs): VAEs are a type of deep learning architecture that can be used to synthesize data. They work by learning a compressed representation of the input data and then using this representation to generate new data that is similar to the input data. VAEs can be used to generate synthetic data that can then augment real data or to fill in the missing information.

From marketing and operations to customer service, the applications of AI are nearly endless. Here are just a few examples of how AI is currently being utilized:

Automation: AI can automate repetitive, time-consuming tasks such as data entry, document processing, and customer support, freeing up employees to focus on more strategic and creative work.

Chatbots: Using a combination of natural language processing, machine learning, and AI to understand customer requests, chatbots are a common way for customers to seemingly interact directly with a company. This allows companies to streamline customer service processes and free up employees’ time to address issues that do in fact require a human touch. 

Product Reccos: Tracking customer behavior through AI empowers companies to recommend products that align with customers’ interests, ultimately keeping them engaged longer. Netflix is a great example of a company that does this well. By analyzing the types of movies and shows most frequently clicked on, this streaming platform encourages customers to stay on for longer periods by presenting them with suggestions similar to what’s been previously viewed.

Audience Segmentation: We all know the saying “know your audience,” but few tools help you truly understand your audience like AI. By segmenting web traffic into clear demographics, companies can predict how customers will receive specific advertisements and create targeted ad campaigns accordingly. 

Supply Chains: If you’re struggling to consistently deliver products on time, AI could become your new best friend. AI-driven solutions can assist companies by predicting just about everything from the price of materials and shipping costs to estimating how fast products will become available, helping to optimize supply chain efforts across the board. 

Companies have been—and will continue to—find innovative ways to help their businesses perform by embracing AI. Overall, AI has the potential to significantly streamline business operations, allowing companies to produce higher-quality work and work more efficiently. But is this automation a threat to critical thought, or worse, the replacement of humans everywhere?

While some applications of AI involve automation, there are plenty of processes being done by humans that aren’t likely to ever become obsolete or replaced by machines. It's important to note that AI is not a replacement for human creativity and expertise, and many aspects of business dealings will still require human input and decision-making. Additionally, an over-reliance on AI can have its drawbacks. While public-facing use of AI can provide rapid service, some customers may still prefer a human touch and feel disconnected from a business depending heavily on AI.

When it comes to internal uses of AI, data bias should be considered. AI algorithms are only as unbiased as the data their trained on. If the input information is biased or incomplete, the AI will be as well, potentially leading to unintended consequences. 

So there we have it. Thoughtfully utilized, AI can be a powerful tool, potentially leading to more informed decision-making, better outcomes, and seamless optimization.