人工智能和区块链如何改变行业并创造创新和增长的新机会

人工智能 (AI) 和区块链技术的交叉正在改变各行业的商业模式，释放新的创新和增长机会。从金融服务到房地产，人工智能正在重塑传统做法，使企业能够提供新服务并简化运营。

AI Impacts Financial Inclusion, Real Estate Sales Processes

人工智能影响金融包容性、房地产销售流程

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.

人工智能对金融领域最重要的影响之一是它能够为服务不足的人群提供金融服务。传统的银行系统通常依赖信用评分和身份证等因素来确定贷款或账户的资格。然而，许多人，尤其是发展中地区的人，无法获得这些证书，从而被排除在金融体系之外。

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

人工智能正在通过提供创新的解决方案来弥补这一差距，使金融机构无需传统形式的身份识别即可评估个人的信用度。

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 首席产品官兼 Sprout AI 实验室负责人 Gian Paulo Dela Rama 在菲律宾曼达卢永举行的 2024 年未来技术峰会上所解释的那样，“对于金融业来说，它为该行业所做的最重要的事情之一就是为金融业提供银行服务。没有银行账户。因此，对于无法获得信贷、无法获得身份证件（银行申请的传统来源）的人，您现在可以使用人工智能工具对这些人进行信用评分。因此，他们现在将有资格获得通常无法获得的金融服务。”

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.

这种金融服务的民主化对于那些生活在银行基础设施有限的地区的人们来说意义重大，因为人工智能使金融机构能够将其服务范围扩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.

人工智能还有助于增强房地产行业的销售流程，而不是取代房地产经纪人。通过使用人工智能工具来识别销售人员的关键技能，房地产公司可以优化其团队以获得更好的绩效。

“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.

“在房地产领域，人工智能正在通过识别销售人员的真正技能来提供帮助。所以，如果你是一个更接近的人，那么你就会被录用。但其他部分，你可以将其自动化，”AI Business Solutions 联合创始人 Valerie Fischer 分享道。这种转变使公司能够自动化日常任务，同时专注于雇用具有专业技能的个人，例如完成交易，这是销售成功的一个关键方面。在这种背景下，人工智能是人类才能的推动者，而不是替代者。

AI Integration Challenges: Data Quality, High Costs

AI 集成挑战：数据质量、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.

虽然人工智能提供了跨行业的新解决方案，但其全部潜力往往受到对准确和透明数据的需求的限制。人工智能系统通常接受大量数据的训练，但验证这些数据的质量和真实性可能是一个挑战。

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.

区块链技术以其不可变且透明的账本，有可能通过确保输入人工智能系统的数据既可信又可验证来解决这个问题。

“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.

“现在人工智能的一个大问题是它需要吸收大量数据进行训练。我们确实没有办法验证传入的内容是否确实是垃圾。如果有一种类似区块链的方式来获取数据、预先检查数据、验证数据……这将会有很大帮助，”Dela Rama 说。

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，区块链解决了与训练人工智能模型相关的高成本问题。通过分散训练过程，区块链使分布式系统能够分担计算负担。 Kaia DLT 基金会的高级业务开发经理 Paolo Caperig 指出：“通过区块链，您可以分散模型的训练……甚至设备也可以用作训练中心。”这可以使人工智能开发更具成本效益和可扩展性，减少小型企业和初创企业的进入壁垒。