人工智慧和區塊鏈如何改變產業並創造創新和成長的新機會

人工智慧 (AI) 和區塊鏈技術的交叉正在改變各行業的商業模式，釋放創新和成長的新機會。從金融服務到房地產，人工智慧正在重塑傳統做法，使企業能夠提供新服務並簡化營運。

AI Impacts Financial Inclusion, Real Estate Sales Processes

人工智慧影響金融包容性、房地產銷售流程

One of the most significant impacts of AI in the financial sector is its ability to provide financial services to underserved populations. Traditional banking systems often rely on factors like credit scores and IDs to determine eligibility for loans or accounts. However, many individuals, especially in developing regions, lack access to these credentials, leaving them excluded from the financial system.

人工智慧對金融領域最重要的影響之一是它能夠為服務不足的人群提供金融服務。傳統的銀行系統通常依賴信用評分和身分證等因素來確定貸款或帳戶的資格。然而，許多人，尤其是發展中地區的人，無法取得這些證書，因而被排除在金融體系之外。

AI is bridging this gap by offering innovative solutions that allow financial institutions to assess the creditworthiness of individuals without traditional forms of identification.

人工智慧正在透過提供創新的解決方案來彌補這一差距，使金融機構無需傳統形式的身份識別即可評估個人的信用度。

As Gian Paulo Dela Rama, Chief Product Officer and Head of Sprout AI Labs at Sprout Solutions, explained at the Futureproof Tech Summit 2024 in Mandaluyong, Philippines, “For finance, one of the most important things that it’s doing for the sector is banking the unbanked. So, people who don’t have access to credit, who do not have access to IDs—your traditional sources of bank applications—using AI tools, you can now credit score these individuals. So they will now be eligible for financial services they normally wouldn’t have.”

正如Sprout Solutions 首席產品長兼Sprout AI 實驗室負責人Gian Paulo Dela Rama 在菲律賓曼達盧永舉行的2024 年未來技術高峰會上所解釋的那樣，「對於金融業來說，它為該行業所做的最重要的事情之一就是為金融業提供銀行服務。因此，對於無法獲得信貸、無法獲得身分證件（銀行申請的傳統來源）的人，您現在可以使用人工智慧工具對這些人進行信用評分。因此，他們現在將有資格獲得通常無法獲得的金融服務。

This democratization of financial services is significant for those living in regions with limited banking infrastructure, as AI enables financial institutions to expand their reach to previously excluded populations.

這種金融服務的民主化對於那些生活在銀行基礎設施有限的地區的人們來說意義重大，因為人工智慧使金融機構能夠將其服務範圍擴大到以前被排除在外的人群。

AI also helps enhance sales processes in the real estate sector rather than replacing real estate agents. By using AI tools to identify the key skills of salespeople, real estate firms can optimize their teams for better performance.

人工智慧也有助於增強房地產行業的銷售流程，而不是取代房地產經紀人。透過使用人工智慧工具來識別銷售人員的關鍵技能，房地產公司可以優化其團隊以獲得更好的績效。

“In real estate, AI is helping… by identifying the real skills of the salespeople. So if you’re a closer, then you’re hired as that. But then the other parts, you can just, automate that,” Valerie Fischer, co-founder of AI Business Solutions, shared. This shift allows companies to automate routine tasks while focusing on hiring individuals with specialized skills like closing deals, which is a key aspect of sales success. In this context, AI serves as an enabler of human talent rather than a replacement.

「在房地產領域，人工智慧正在透過識別銷售人員的真正技能來提供幫助。所以，如果你是一個更接近的人，那麼你就會被錄用。但其他部分，你可以將其自動化，」AI Business Solutions 聯合創始人 Valerie Fischer 分享道。這種轉變使公司能夠自動化日常任務，同時專注於僱用具有專業技能的個人，例如完成交易，這是銷售成功的關鍵方面。在這種背景下，人工智慧是人類才能的推動者，而不是替代者。

AI Integration Challenges: Data Quality, High Costs

AI 整合挑戰：資料品質、高成本

While AI provides new solutions across industries, its full potential is often limited by the need for accurate and transparent data. AI systems are typically trained on massive amounts of data, but verifying the quality and authenticity of this data can be a challenge.

雖然人工智慧提供了跨行業的新解決方案，但其全部潛力往往受到對準確和透明數據的需求的限制。人工智慧系統通常接受大量資料的訓練，但驗證這些資料的品質和真實性可能是一個挑戰。

Blockchain technology, with its immutable and transparent ledger, has the potential to address this issue by ensuring that the data feeding into AI systems is both trustworthy and verifiable.

區塊鏈技術以其不可變且透明的帳本，有可能透過確保輸入人工智慧系統的資料既可信又可驗證來解決這個問題。

“A big problem with AI now is that it ingests so much data to train. There’s really no way for us to verify if what is coming in is actually garbage or not. If there’s a blockchain-like way of ingesting the data, having the data checked beforehand, having the data verified… that will help a lot,” Dela Rama said.

「現在人工智慧的一個大問題是它需要吸收大量資料進行訓練。我們確實沒有辦法驗證傳入的內容是否確實是垃圾。如果有一種類似區塊鏈的方式來獲取數據、預先檢查數據、驗證數據……這將會有很大幫助，」Dela Rama 說。

Moreover, blockchain solves the high costs associated with training AI models. By decentralizing the training process, blockchain enables distributed systems to share the computational burden. Paolo Caperig, Senior Business Development Manager at Kaia DLT Foundation, noted, “With blockchain, you can decentralize the training of the models… even the devices can be used as training hubs.” This could make AI development more cost-effective and scalable, reducing the barriers to entry for small businesses and startups.

此外，區塊鏈解決了與訓練人工智慧模型相關的高成本問題。透過分散訓練過程，區塊鏈使分散式系統分擔計算負擔。 Kaia DLT 基金會的高級業務開發經理 Paolo Caperig 指出：“透過區塊鏈，您可以分散模型的訓練……甚至設備也可以用作訓練中心。”這可以使人工智慧開發更具成本效益和可擴展性，減少小型企業和新創企業的進入障礙。