Kamales Lardi is CEO of Lardi & Partner Consulting GmbH and a global award-winning expert in digital business transformation.
Technology is advancing at an exponential rate resulting in announcements of breakthrough solutions almost every week. The transformative impact of technologies such as blockchain and generative artificial intelligence (AI) can be seen in almost every aspect of business and our lives. These technologies have become indispensable across various domains ranging from healthcare to entertainment. However, as powerful as each technology is, the convergence of emerging technologies can create remarkable potential benefits and advantages.
Blockchain provides a decentralized and secure way to store and share information, while generative AI allows self-learning and creativity in machines. By combining the two technologies, enhanced systems can be created that are secure but also intelligent and adaptive. Organizations are looking toward these systems to prevent data breaches, increase efficiency and reduce costs. Although the development of each technology drives transformation, the convergence of these technologies can offer far greater potential across industries and businesses.
AI is a crucial emerging technology that could help organizations reimagine consumer experiences and business processes, as well as unlock revenue growth and cost savings at an exponential scale. Data is the foundation of artificial intelligence systems and is a prerequisite for successfully implementing AI solutions. Organizations must determine, among other things, whether the data is balanced (free of bias), exhaustive (includes all pertinent variables), diverse (includes rare situations) and of sufficient volume. Typically, I advise businesses to develop an effective data strategy at the outset of AI implementation, including the definition of data requirements, the collection or acquisition of high-quality, contextual data and the storage, management and security requirements.
In the current digital economy, data is produced exponentially by people, channels, platforms and devices. In addition to the large amounts of data that could be analyzed, I noticed that there still exist silos that make it hard to combine data points to derive insights. AI models used for decision making provide little transparency, where large data sets are pumped into systems, and results are produced in the form of analysis, reports or recommendations. This can create an issue of trust and raises questions about the system’s credibility, particularly considering the existing challenges with data sets that may be incomplete, poorly sourced, inaccurate or contain biases.
However, combined with blockchain technology that offers clear data provenance and audit trails, transparency and traceability of data and potential interoperability across various platforms, I believe the result could produce more trustworthy AI-based systems for analysis and decision-making.
Blockchain is a digital technology that enables secure and transparent transaction record-keeping. Imagine it as a digital ledger, similar to an accounting book, but instead of being stored in a single location, it is dispersed across numerous computers worldwide. This decentralization increases the system’s security and makes it less susceptible to manipulation. In recent years, advancements in blockchain technology have been at the forefront of innovation across various industries. Although blockchain technology is often described in relation to the financial services industry and cryptocurrencies, its potential application across industries to create trust, traceability, transparency and provenance in the transfer of value can be transformative. My experience in designing and implementing a blockchain solution for the palm oil supply chain formed my belief that this technology will transform industries in the near future (described in my book The Human Side Of Digital Business Transformation).
With the application of blockchain as a framework for data storage, AI systems can operate in a decentralized and secure environment, with each block containing a unique identifier and cryptographic hash. This ensures that data is tamper-proof and transparent, giving users greater control over their personal information and the confidence to trust the system in question. Smart contracts (digital, programmable and self-executing contracts written into the blockchain) can facilitate transparent and automated agreements between AI systems, improving efficiency and minimizing the potential for errors. By combining blockchain technology with generative artificial intelligence-based systems, businesses could unlock new operational value and efficiencies.
Generative AI could positively benefit blockchain solutions by automating the creation of smart contracts, reducing the time and effort required to conduct transactions. The result–quicker and more efficient contract execution, as well as increased accuracy and transparency. In addition, generative AI could be utilized to form decentralized autonomous organizations (DAOs), self-governing entities that foster innovation and creativity. Establishing a symbiotic relationship between blockchain and generative AI can create an ecosystem that supports multiple industries, including the financial sector, healthcare and supply chain management. Integrating blockchain technology with generative artificial intelligence-based systems can bring immense benefits, ranging from improving the speed and security of transactions to enabling new business models and creating innovative products and services.
I believe the integration of generative artificial intelligence with blockchain technology has the potential to develop trustworthy and secure blockchain systems. AI can aid in identifying and preventing fraudulent activities within a blockchain network, thereby improving traceability and transparency and mitigating the risks of security breaches by providing a robust surveillance system that detects vulnerabilities and responds swiftly to cyber threats. By automating complex processes, AI-based solutions such as robotics process automation can also contribute to the scalability and efficiency of blockchain systems.
The convergence of these technologies could transform numerous industries, including supply chain management, financial services and healthcare. However, maturity and adoption are still in their infancy, particularly in terms of the development of applicable standards, regulations and best practices. This could potentially result in unforeseen legal and compliance issues. For example, although blockchain provides data immutability and transparency, Al algorithms often require significant data sets, raising data privacy and security concerns.
Both technologies are also resource-intensive, requiring significant processing power. Additionally, scaling blockchain networks could result in performance and latency issues, further exacerbating the problem when converging AI-based applications that often need to process significant amounts of data.
As we progress, the combination of emerging technologies produces new solutions that not only leverage the benefits of each technology but also accelerate solutions to achieve new levels of efficiency, performance, human capability, societal outcomes and business results.
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