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The influence of AI is expanding at a breathtaking pace, disrupting many sectors with innovative applications that simplify and enhance various aspects of human life. Research shows that the global AI market size is expected to grow 37% annually from 2023 to 2030.
From the rise of conversational AI like ChatGPT to its impact on banking, healthcare, and data analytics, AI's influence is indisputable. This article will explore how AI is reshaping the banking and healthcare industries. You will learn about:
Artificial intelligence is a field of computer science that deals with creating systems that can simulate human intelligence processes. The system employs intelligent algorithms built into a dynamic computing environment to simulate these human intelligence processes while actively learning and improving output.
Since it was first mentioned in 1950, AI has gone through many stages of development. This rapid adoption is attributed to its usefulness and how it simplifies human activities. From implementing the Eliza chatbot, facial recognition, deep fakes, and autonomous vehicles to content and image creation, AI trends aren't ending soon. Currently, AI democratization is making it easier for people to build AI solutions in various industries. This is possible by merging the No-code/Low code software development methodology with AI implementation.
Additionally, other trends like AI-augmented analytics have made headway in recent times. But, the primary trend discussed lately is the rise of generative AI.
The Generative AI conversion is fueled by the rise of OpenAI's ChatGPT. With few English queries, technical and nontechnical users could interact and generate solutions to problems. So far, many fields have integrated generative AI capabilities into their solutions. We have seen analytics tools with these generative AI features, like the Kyligence Zen and Bing Copilot.
AI is applied in banking for revenue forecasting, stock price predictions, risk monitoring, financial advisory, and fraud detection. Let's explore two of these fields with examples.
AI robo-advisors provide investors and individuals with selected financial services using predefined algorithms. Like a financial advisor, the robo-advisor will collect user information and analyze it with sophisticated software and algorithms. Lastly, it will deliver a diversified portfolio of exchange-traded or index funds that suit your profile. You can select the best investment while the AI rebalances the portfolio. An example of such Implementation is Wealthfront, a robo-advisor that uses advanced algorithms to create and manage diversified portfolios for its users. The AI-powered tool offers tax-loss harvesting and direct indexing to optimize after-tax returns.
The ability to analyze vast datasets and identify relationships, trends, and anomalies is what's driving the implementation of AI for fraud detection. Banking institutions can connect their data, and the AI tools will analyze users' behavior and activities against predefined fraudulent patterns. Not only does this allow banks to identify fraud, but it also helps the analyst save time and boost productivity. An example of an AI for fraud detection is the ZignSec solution.
The Healthcare industry has had its fair share of AI disruption with applications in diagnosis, health assistance, remote monitoring, and more.
With AI adoption in healthcare, doctors and other practitioners can generate patient diagnoses faster. For example, in a recent study, AI models provided with MRI-scanned images achieved an accuracy of 98.56% in brain tumor classification. With this feature, doctors are notified of early signs of large vessel occlusion stroke, enabling them to create a treatment plan or observe the patient.
AI-powered Virtual assistant provides support to patients and answers queries 24/7. Integrating these tools into your business workflow allows you to free time for other administrative activities. An example of a virtual assistant is the Docus AI health assistance that answers your questions. There's also an option to contact doctors to verify answers from the tools, get disease probability, and many other options. Since searching on Google doesn't give specific answers, this tool takes patient care to the next level.
Telehealth and remote monitoring allow doctors to track outpatients' status, especially those with heart and other chronic conditions. Research has also revealed that about 70.6 million Americans will use these RPM tools by 2025. Additionally, another study by the Mayo Clinic showed that in 2021, COVID-19 patients who participated in an RPM program had few ER visits & hospitalization rates. These AI-powered tools used machine learning algorithms to monitor and analyze data from wearable devices and extract clinically relevant information. The platforms can also provide real-time feedback, predictions, and more. An example is Biofourmis virtual care management service, which uses analytics, AI, and wearables to monitor patients' complex chronic conditions remotely.
Goldman Sachs Group recently explained the impact of AI across various industries in their report. In the report, they reveal that Construction and extraction, installation, maintenance, and repair, and Building and grounds cleaning and maintenance will have lesser AI impact. The percentage of AI implementation in these sectors ranges from 1% to 7%. Industries, where most activities require a human expert and manual labor, will maintain relevance. AI tools might come in as a commentary solution in these industries. However, the disruption will be minimal compared to administrative sectors, with repeat tasks easily automated with AI.
Like other industries, AI tools are helping businesses automate data analysis tasks for improved productivity. The adoption and creation of AI-powered analytics tools like the Kyligence Zen and Kyligence Copilot have accelerated data analytics due to their benefits. Generally, AI tools like Kyligence disrupt 3 significant segments of data analytics processes.
Quick Insights Discovery: With the help of AI Copilot, Kyligence Zen allows for the uncovering of hidden insights within minutes, making data analytics more efficient and affordable.
Intuitive Interactions: Kyligence Copilot, when combined with Kyligence Zen, facilitates intuitive, dialogue-driven data interactions, ensuring insights are accessible to all, regardless of technical acumen. This evolution in data engagement helps in analyzing large datasets effectively and swiftly.
Transcending Traditional BI Limitations: Kyligence Zen helps transcend the limitations of traditional business intelligence (BI) reports, aiding in true, metrics-driven decision-making.
Automated Data Storytelling: AI can augment data presentation by synthesizing insights and findings from data, a concept referred to as automated data storytelling. This enhances the depth and context of data presentation.
Ease of Use: The low-code nature of Kyligence Zen makes it easier for users to pull data into pre-built templates for analysis without needing to write complex code or SQL queries.
The AI disruption across different industries has been nothing short of innovative growth. Although these tools have limitations and ethical concerns, they will be refined, upgraded, and better. Rather than ignore its usefulness or try to fight it, we should see AI as a complementary solution for improved productivity.
Do you want to integrate an AI-augmented data analytics tool in your business workflow? Sign up on Kyligence Zen for free and start chatting with your data for deeper insights.
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