Business Intelligence Robot – There is so much data out there today that it is causing a lot of anxiety among office workers, business leaders want robots to make decisions for them.
Some 74% in Asia-Pacific say the number of decisions they make each day has increased tenfold over the past three years, with 86% citing that the volume of data has made decisions at work and in life more complex. Another 89% said the inability to make decisions was creating a negative impact on their quality of life, revealed a survey by Oracle in partnership with DKC Analytics.
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With so much information out there, 33% said they don’t know which sources or data to trust and feel overwhelmed, while 71% have simply given up on making decisions. The study surveyed 14,000 employees and business leaders worldwide, including 4,500 from six Asia-Pacific markets: Singapore, Australia, South Korea, China, India and Japan.
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Among information overload, 92% said they have changed the way they make decisions in the past three years, with 31% relying entirely on gut feelings. Some 96% sought help from existing data but believed they lacked the skills to interpret the information in a meaningful way.
Overwhelmed by the volume of data, 85% of business leaders let a robot make their decisions and avoid the challenges that arise.
Some 87% admitted to suffering from “decision-making difficulties”, regretting or feeling guilty about decisions they had made in the past year. Another 73% said a lack of confidence in the data and the amount of data kept them from making a decision.
And while business leaders in the region recognize that data is critical to their company’s success, the majority feel they lack the right tools to use it.
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The survey found that 74% said dashboards and charts were not directly related to the decisions they made, with 77% describing the most available data as helpful only for IT professionals or data scientists.
Some 47% said managing different data sources required additional resources to collect all the data, while 38% said it slowed strategic decision-making. Another 31% created more opportunities for error due to managing different data sources.
However, 97% believed that accurate information and insights could help them make better HR (human resources) decisions, while 95% and 93% said the same for supply chain and finance-related decisions, respectively.
Some 43% wanted data to help them make better decisions, while 37% wanted it to reduce risk and 30% wanted data for contingency planning.
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Without information, 45% of respondents said their decisions would be less accurate, while 41% said they would be prone to error.
“As businesses expand to serve customers in new ways, the number of data inputs required to get the full picture expands,” said Chris Cheliah, senior vice president of technology and customer strategy for Asia-Pacific Japan at Oracle. “The hesitancy, mistrust and lack of understanding of the information shown in this study is consistent with what we’re hearing about consumers rethinking their decision-making process.”
Related Best Robot Vacuum Mops: Best AI Chatbots Tested by Experts: ChatGPT Isn’t the Only One to Try Want to be a data scientist? Do These 4 Things According to Business Leaders In the rapidly evolving technology landscape, two titans stand at the forefront: business intelligence (BI) and artificial intelligence (AI). These are not just rumours; They are revolutionizing how we interact with data and make decisions. In a world full of data, understanding the distinct roles and capabilities of BI and AI is more than an intellectual exercise—it’s a business imperative. But what separates them? How do these technologies shape the future of data-driven decision making? This post dives deep into the heart of this important question by dissecting the key differences between business intelligence and artificial intelligence. Whether you’re a seasoned technology professional or simply curious about the future of business technology, this exploration is for you.
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The journey into the realm of BI and AI begins with their core objectives. Experienced in data analytics with business intelligence tools, adept at dissecting past and current data to extract actionable insights. They turn vast data lakes into understandable reports and dashboards, helping businesses understand where they stand. On the flip side, artificial intelligence represents an ambitious upstart. AI doesn’t just analyze data; learn from it. With AI, we’re not just looking at what has happened – we’re predicting what might happen next. Imagine a technology that not only tells you your sales decline in the last quarter but also predicts future market trends and suggests proactive strategies. This is AI in action, a bold step towards not just understanding but shaping the future.
Data, in its raw form, is like a diamond in the rough. BI polishes this diamond by processing structured data — neatly arranged in tables and charts. It’s about bringing order to numbers and statistics, understanding sales records, financial statements and customer information. However, AI relies on diversity. It dives into the chaotic world of unstructured data — from the words of these blog posts to social media chats, images and beyond. AI’s ability to interpret these diverse data types opens up new frontiers in understanding human behavior and market trends, beyond the reach of traditional BI tools.
When it comes to decision making, BI and AI take distinctly different approaches. Business intelligence tools are like historians; They excel at providing descriptive insights. They look back, through historical data to tell you what happened and why. Think of a comprehensive report detailing last year’s sales trends – that’s BI at its core. In contrast, AI is visionary. It’s less about looking back and more about looking forward. AI employs predictive modeling, using data not just to explain, but to predict. It’s like having a crystal ball, using algorithms and machine learning to predict market changes, customer behavior and even potential operational problems before they happen.
User interaction is another area where BI and AI diverge. Business intelligence is synonymous with static reports — reliable, consistent, but largely immutable. These reports are invaluable for regular review and tracking of key performance indicators. But AI? It is dynamic, constantly learning and adapting. Each new piece of data is a learning opportunity, enabling AI systems to evolve their understanding and recommendations This dynamic nature of AI opens the door to personalized customer experiences, real-time decision making and adaptive business strategies that can pivot as the market changes.
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Implementation is where the practicality of these technologies comes into play BI systems are relatively user-friendly, designed with business users in mind. They integrate with existing databases and offer intuitive interfaces that non-tech professionals can easily navigate. Conversely, implementing AI is a more complex beast. This often requires specialized knowledge in data science and machine learning algorithms. AI systems aren’t just plug-and-play; They require fine tuning and continuous adjustment to align with specific business goals and datasets. This complexity, however, brings unparalleled customization and power to those who master it.
Cost and return on investment (ROI) are important factors in any technology decision. BI tools, with their simpler implementations and established track records, often present a clearer initial investment and ROI path. These are like a solid investment in a tried and tested stock – you know what to expect. AI, however, is like a venture capital investment. Initial costs can be high due to complexity and the need for specialized talent. But the potential long-term benefits – from automating routine tasks to unlocking new business insights – could be game-changing. This is a high risk, potentially high reward scenario.
In conclusion, understanding the difference between business intelligence and artificial intelligence is key to effectively utilizing these technologies. While BI provides reliable, structured analysis of past and present data, AI opens the door to predictive insights and dynamic decision-making. Each has its own strengths, complexities and role in the data-driven landscape of modern business. As technology continues to evolve, the synergy between BI and AI will become a critical component of successful business strategies, blending the stability of business intelligence with the innovative potential of artificial intelligence.
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