Adopting AI for Improved Business Growth

The evolution of artificial intelligence (AI) is well underway, as the AI market already reached a $95 billion valuation in 2021. Experts expect that amount to grow twentyfold by 2030 to nearly two trillion dollars. With such funding, numerous industries will feel the disruptive impact of artificial intelligence.

But such a rapid shift towards thinking computer systems raises several questions. Does AI hurt or help your business? Is this a helpful innovation or just a fashionable, yet meaningless trend? How should you incorporate AI into your operations? Speculation about the technology abounds.

Let’s explore the advantages and pitfalls of artificial intelligence. A complete overview of the topic can show how you can best adopt AI to maximize your business potential.

There is a reason why the interest in AI reached an all-time high in 2023: machine intelligence can enhance productivity. Intelligent systems have cognitive insight, or the ability to interpret and understand unstructured data. AI algorithms can reevaluate its data (aka, learn from itself) to earn better conclusions. That type of analysis is far beyond the static work of general tech.

As a result, intelligent systems offer several business productivity benefits, such as:

Cognitive reasoning doesn’t just develop insights into rote data. Instead, it generates insights and outcomes collected from undefined information. That type of data reading augments the limits of human understanding. AI-powered data processing offers nuanced perspectives, and that results in well-rounded choices.

Netflix offers a perfect example. The company is well known for the use of personalization engines and AI-powered testing. Both tools help facilitate both customer and C-suite decisions. As a result, the content provider has experienced continued subscriber growth (235 million users) over the past ten years.

We all know how automation provides a low-cost way to complete monotonous tasks. But AI doesn’t just execute repeat tasks, it improves upon them. For example, intelligent algorithms can anticipate sudden changes in demand, smartly identify bottlenecks, and optimize supply routes. Such data-based refinements introduce massive industry-specific efficiency and cost savings. In short, smart machines can overhaul all your processes, end-to-end. Gartner predicts that artificial intelligence will eliminate 90 percent of product management functions by 2030.

AI uses algorithms to analyze sentiment polarity and natural language within thousands of different contexts. Such complex insights allow cognitive computers to understand customer behavior at levels far beyond general tech. That offers massive benefits with customer support, recommendations, or product personalization. For example, Walmart used AI deep learning to analyze aggregate customer data (size, type, brand, price, preference). The digital assistant then offers secondary items for a desired out-of-stock product. Upon deployment, customer acceptance of substitutions increased to over 95 percent. It is an ideal way to maintain customer happiness.

AI systems learn from vast historical data to improve real-time resource allocation. For example, intelligent distribution can help predict maintenance schedules, minimize waste, or schedule inventory shipments. The algorithms assess data within your determined constraints, which leads to a faster speed of business. Deloitte reports of public hospitals in Australia that use AI-powered patient admissions and bed availability. As a result of improved resource use, the hospital system there is saving US$2.5 million a year.

AI excels at tracking non-linear patterns or dependencies. AI systems can even assign probabilities to uncertainties or multiple variables on a single data point. That greatly improves predictions compared to basic data analysis. Your business can then generate models for numerous use cases (product development, sales, trends tracking, etc). As an example, Shell uses AI to predict the risk of compressor failures 24-48 hours in advance. That results in vastly improved maintenance and business service uptimes.

Standard fraud solutions can collect data on numerous transactions. But AI improves upon collected data for greater accuracy in determining suspicious behavior. That helps reduce false positives, improve risk profiles, and catch suspicious activity. For example, Paypal uses machine learning in its Fraud Protection Advanced program. Out-of-box filters proactively adjust to fraud trends. As a result, Paypal has historically been known for fraud rates far below the eCommerce industry average.

Clearly, cognitive insight introduces game-changing advantages to your business. But AI is not a golden ticket to higher revenues with zero aftereffects. The technology does create several ethical considerations that may negatively impact your business. Before you rush into using intelligent systems, it is good to acknowledge the following business concerns:

AI magnifies the use and value of personal information. That raises privacy concerns. Issues of customer consent and unlawful surveillance are certainly relevant. And as privacy laws change, AI can introduce compliance difficulties you must prepare for.

Of course, much of the privacy worries stem from the popular myth that AI is a self-aware global control system. That misconception is likely due to popular culture portrayals of sentient robots. In reality, AI requires human oversight and cannot develop beyond its code (in other words, world domination by computers is just  a good story). Synthetic intelligence is simply a tool designed and built to augment human capabilities.

AI makes decisions from human-provided training data. If that data set includes inherent biases, your intelligent system can amplify discriminatory or unfair practices. That exposes you to legal risks, loss of customer trust, and lack of inclusivity.

The problem of bias also exposes the myth that AI is omniscient. Many consider AI as perfect, infallible tech since it can learn from itself. In reality, AI produces many incorrect results and can exacerbate internal inconsistencies. Intelligent systems – an innovative marvel in its own right – cannot replicate human creativity, nuance, or emotion.

Deep neural networks operate beyond human capacity. While of great use, such tech can also suffer from a lack of explainability. AI can work in a “black box,” where the inner workings of an algorithm are hidden and unknown. But hidden operations raise several issues of accountability. Who is responsible for unknown mistakes made by AI?

Such AI mysticism also drives another common myth: that AI can solve all of the world’s problems. But when you look behind the curtain, AI always operates within the limits and boundaries of data systems. Intelligent machines are not a magical antidote to our problems—they merely support the expertise and judgment of humans.

AI will radically change the nature of labor. On a positive note, that means intelligent systems can aid and upskill employees. On the other hand, AI can also cause job displacement. For example, automated computing eliminates routine-based jobs typically used as an entry point for employees in the field. That also places greater emphasis on AI-assisted roles that demand greater skill. Such changes, if left unaddressed can fracture your current office culture.

It also creates another myth, where AI will replace all human labor. In reality, AI algorithms cannot replace the human brain. Machine intelligence will not render humans obsolete, but instead will actually improve the value of human work.

Artificial intelligence promotes a data-driven culture. That can lead to a widening of the digital divide. Smart machines can strengthen current social inequalities.

But we can avoid many of these social consequences with efforts towards education and access. Much of the digital divide is simply due to an incorrect understanding of AI. Many consider learning machines as an expensive tool reserved for large corporations with teams of scientists. In reality, ready-made AI solutions are available to all types of businesses. We all use smart tech daily, from traffic apps to search engines.

Do AI users have an ethical responsibility? Can we teach AI to encode certain values? Can it be manipulated (and is thus a security concern)? For example, many have noted Tesla’s use of AI within its self-driving cars. That brought numerous concerns about hacking, safety, and responsibility (who’s at fault during a crash committed by an AI-driven car?). Such topics about the control of AI are still hotly debated.

Despite the valid ethical concerns AI raises, the “gold rush” of AI is occurring. Total investment in smart machines is up sixfold from 2016, to $92 billion in 2022. Government and corporate training initiatives are well underway.

As a result, adoption rates skyrocketed. The IBM Global AI Adoption Index shows stable growth, with more than a third of companies reporting intelligent systems use. More and more people are turning to AI.

That introduces an opportunity cost. If you don’t integrate AI, you miss out on its benefits in addition to running the risk of falling behind. Early adoption is crucial, for the following reasons:   

• Learning time: Artificial intelligence takes time to integrate. You must supply a wealth of data before your AI system can function well. Plus, rulesets always need improvements, a process that can take years. You drastically improve your return on investment timeline with early adoption.

• Competitive advantage: Second, early adopters gain the advantage of innovation. AI creates new products and services beyond standard tech— that allow you to redefine your industry. Just look at how generative AI changed Google’s search engine operations. And that’s without mentioning the impact of personalization AI offers on the customer experience.

• Market shifts: Those who adopt AI early earn greater agility. That is crucial as the shift into digital experiences accelerates. For example, early adoption makes it far easier for you to adjust to incoming regulations. And effective AI will be necessary for new security threats, which will also grow in sophistication. Those who wait to address such concerns will face growing barriers to entry.  

Skill shortages: Lastly, early adoption can help you address the talent shortage. The AI industry will continue to battle a skills crisis, and new training cannot keep pace with industry growth. Early adoption gives you access to current talent and time to train your own employees.

Luckily, you don’t need to revamp your entire IT department to leverage AI today. There are plenty of services that offer a fast ROI and help you transition toward intelligent systems:

• Customer support AI: Use conversational AI programs to support service reps and deliver personalized customer experiences. Chatbots, multi-language tools, sentiment analysis, and augmented messaging can all embed into the service teams.  

• Demand and sales forecasting AI: Predict the market with AI forecasting models. AI will weigh factors such as seasonality, trends, historical sales, holidays, and customer segments. Improved accuracy will give you greater control over inventory, resource allocation, and production processes.

• AI-based fraud detection: Select fraud services that utilize AI. Machine learning offers real-time analysis, advanced pattern recognition, and risk-scoring algorithms. Intelligent systems vastly improve the accuracy and adaptability of standard fraud protection.

• Natural Language Processing (NLP): Use natural language processing algorithms to handle labor-intensive administration tasks. NLP such as Google Cloud Natural Language Processing or Amazon Comprehend can summarize lengthy texts, engage in customer question and answer, classify documents, and employ entity recognition. Such language comprehension improves manual information processing within your business.

AI-based chargeback mitigation: Transform your chargeback management strategy with AI-based tools. For example, Justt uses a self-improving AI machine to build custom chargeback solutions for your business. As a result, data insights improve payment process bottlenecks that would normally result in chargebacks. And intelligent systems rapidly and automatically collect dispute evidence, scaling defenses according to transaction volume. Artificial intelligence can directly support chargeback support teams and help you win back lost revenue.

The AI revolution is key to your success, both now and in the future. Those that wait to adopt AI may never catch up. If you are ready to leverage the benefits of smart tech, here are some key takeaways that should guide your adoption strategy:

• Determine high-impact areas: Prioritize your efforts. AI should deliver concrete value by solving problems your organization faces. Strategic alignment supports your change management, offers quick yet effective wins, and optimizes resources.

• Automate: Build AI processes that can run without your intervention. Algorithms will always need human training, but the end goal is hands-free task execution. That will drive accuracy, scalability, and consistency.  

• Focus on the customer: The customer experience remains the primary competitive advantage. Luckily, artificial intelligence is adept at personalization, a crucial element in achieving higher customer satisfaction levels. Focus your AI adoption on services that revolutionize the customer journey.

• If need be, go low code: Ideally, AI integrates holistically into all aspects of your business. But such efforts are complex. So if you can’t build, buy. Opt for many of the low-code AI options, such as IBM Watson or Google Cloud AutoML.

• Collaborate: Lastly, find a technical partner. The experts can make your AI adoption strategy simple and effective. Use the available services and vendors to earn a better ROI.

Want to quickly incorporate AI into your business? Discover how Justt is an ideal AI-powered chargeback service that can elevate your adoption strategy.