Andriy Sambir, CEO of Linkup Studio.
There are many articles written about the trends in AI. In this one, I’d like to examine ways in which AI may help improve business operations and, in particular cases, why AI should be used with caution and thorough observations. I’ll support my thoughts with firsthand knowledge from my 10 years as CEO of a software development and design company, as well as with some well-known use cases.
Upsides: Where AI Shines
• Intelligent Process Automation
AI tools are driving process automation and optimization for various businesses. By automating repetitive and manual tasks, AI-powered systems greatly enhance operational efficiency and productivity.
For instance, we had a project in the healthcare industry. AI algorithms were used to analyze medical facilities’ records. This collected, linked and verified a vast number of documents and helped a company for healthcare audits reduce countless hours of their workers’ manual document analysis to mere seconds. If your business deals with such constant and monotonous tasks, I believe there is definitely an advantage to utilizing AI.
• Customer Support Chatbots
Conversational AI chatbots provide quick and accurate 24/7 responses to customer inquiries. Various industries like e-commerce, finance and banking use these bots for handling routine queries, allowing their human workforce to tackle more intricate tasks. This can help enhance customer service, shorten response times and uplift the overall customer experience.
For example, Netflix enhanced its customer assistance using AI chatbots. Being capable of comprehending natural language, they can conduct conversations resembling human interaction. They assist customers by leading them through problem-solving procedures or responding to questions about billing. So, AI may be a great opportunity if your business has some direct communication with clients through text chats.
• Data Analytics
AI in data analytics rapidly analyzes vast amounts of data, offering companies essential insights into consumer behavior, market trends, product performance and more. This can aid in making informed decisions and enhancing customer experiences.
For example, in the financial industry, AI can help detect fraudulent activities. Mastercard utilizes AI to scan for suspect transactions. In the last three years, their AI-powered cybersecurity solutions have stopped over $35 billion in fraud losses. If your business holds a large amount of untapped data, AI can help turn it into actionable and sometimes critically important insights.
• Predictive Analytics
AI-driven predictive analytics is redefining the way businesses adapt to future shifts. By leveraging past data and sophisticated machine learning, companies can make precise forecasts that let them address issues before they become problems and take new opportunities as they arise.
For instance, Walmart leverages AI, including predictive analytics, to augment daily supply chain operations, which aids in predicting demand fluctuations, particularly during high or unforeseen customer traffic events. AI and machine learning-based forecasts assist the firm in optimizing its network, ensuring inventory is accurately located and timely as consumers fill their in-store or online shopping baskets. If you aim to create intelligent future projections rooted in historical data and don’t want to spend endless manual working hours, AI tools can be a potent asset for this purpose.
Downsides: Where To Proceed With Caution
• Security Risks
AI-generated code can be riskier than we’d like. Its complexity can baffle even experienced developers, making security issues harder to spot. Learning from flawed datasets, AI might unknowingly replicate these issues. The necessary extensive testing is often skipped due to this complexity, leaving it more vulnerable to cyberattacks than standard code. Such vulnerabilities have led to significant data loss and decreased system effectiveness in some companies.
On August 2, 2023, Elon Musk announced on “X” (Twitter) that Tesla has fully transitioned its Full Self Driving vehicle control to AI neural networks. This move underscores Tesla’s growing reliance on AI, as highlighted in December 2022 by the ex-director of AI at Tesla, Andrej Karpathy. Yet, this technological transition raises security concerns. In a 2019 incident, hackers successfully tricked Tesla’s Autopilot, steering a car into oncoming traffic. This security breach occurred through manual means, but the switch to AI might heighten such threats.
I believe it is better to protect businesses across various sectors from such threats. To do so, I recommend employing and maintaining skilled cybersecurity and AI developers on your team who can help ensure the quality of your organization’s AI-generated code and oversee the proper functioning of AI-based systems and models.
• The Risks Of Over-Reliance
A Gartner survey in 2022 showed that 32% of CIOs are increasing investments in artificial intelligence. This suggests that organizations place trust in AI. However, while these tools aim for automation and efficiency, such ease of use can also have a downside. It may lead to a false sense of security, prompting people to forgo monitoring and oversight, which remain crucial as AI systems are not perfect and do commit mistakes.
For example, my company developed an AI app for identifying skin diseases and aiding in skin cancer prevention via photographs. Despite our efforts to minimize incorrect results, inaccuracies can still happen due to device complications, platform restrictions or other factors. We’ve had to include disclaimers to inform users that AI-generated results are not entirely dependable and that consulting an expert for a conclusive diagnosis is advisable.
This is why it is important to have human evaluators constantly monitoring results produced by AI. Having managers, medical professionals or assigned observers overseeing AI processes can lower the risk of negative consequences that could hinder business growth or even be life-threatening.
• Privacy And Ethics
Privacy and ethics can often get overlooked in AI discussions. If neglected, AI algorithms may unintentionally amplify biases, leading to potential harm or unfair outcomes.
A notable example is Microsoft’s Tay chatbot, released in 2016. Designed to learn from user interactions, the bot was quickly exploited by trolls and began emitting hate-filled and offensive comments within 16 hours of launch. Microsoft swiftly took it offline and discussed the lessons learned in an official blog post.
While chatbots and other AI technologies offer undeniable benefits, as previously discussed, it’s vital to employ them responsibly.
Finding A Balance And Exercising Common Sense
AI is rapidly advancing, offering businesses significant transformative potential. However, it has its limitations. A major lesson from my experience working and negotiating with clients is this: AI can be transformative, but it’s not a magic bullet. Its integration into business processes must be thoughtfully managed while considering its varying benefits and challenges for your unique company and situation.
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