The Rise of Generative AI: Ethical Implementation and Value-Driving Applications
We find ourselves immersed in a never-ending cycle of excitement and anxiety surrounding generative AI. Its various acronyms, such as GPTs, LLMs, and GANs, may confuse non-technologists, but they signify the impact and implications of this technology on the economy, the future of work, and even humanity itself.
When speaking with other CEOs, two primary concerns consistently dominate the conversation: first, the ethical, safe, and secure implementation of these new technologies, and second, how to translate them into practical applications that deliver value to their companies.
Generative AI has become a focal point of public discussions due to its capability to create original content in various forms, including text, images, videos, and code. It surpasses the traditional analytical and predictive capabilities associated with AI. Chatbots powered by generative AI, like ChatGPT and DALL-E, blur the line between humans and computers, streamlining technical and often tedious tasks while significantly enhancing productivity.
It’s no wonder these technologies have captured our collective imagination.
But it’s not just our imagination. According to Pitchbook, annual venture capital investments in generative AI have surged by 425% since 2020, reaching $2.1 billion, with an astounding $11 billion invested in the first quarter of this year alone. As media commentary has highlighted extensively, the potential of these technologies, both for positive advancements and negative consequences, is enormous.
Amidst all the excitement and speculation, it is crucial to address the two fundamental questions at hand.
First and foremost, ethical and regulatory concerns must take precedence. Renowned scientists and AI developers express valid worries about the rapid deployment of AI and its potential risks. The proliferation of new risks, such as cyberattacks, disinformation, fraud, and unrestrained surveillance, arises from the emergence of these technologies.
These risks underscore the importance of prioritizing security. Many generative AI tools, like ChatGPT, are not yet suitable for enterprise-level implementation. Julia de Boinville from Scale AI emphasizes that most organizations will not find off-the-shelf solutions that meet their specific needs. Organizations will need customized approaches to address data security concerns, the need for fine-tuning on proprietary data, and the risk of false or misleading results from these models.
Hence, a cautious and deliberate approach is essential to ensure that we take all necessary precautions.
Secondly, once we establish the appropriate security parameters, it becomes crucial to identify potential use cases for developing and deploying these new technologies. AI already assists us in running businesses more efficiently and productively. The advancement of machine learning algorithms, the interconnectedness and abundance of data, the availability of cloud-based AI services, and the ever-increasing processing power of computers have made these advances possible.
The COVID-19 pandemic, with its disruptive effects on supply and demand, has accelerated the adoption of AI technologies. Systems that provide enhanced visibility, data analytics, and predictive capabilities have become indispensable for forecasting in these uncertain times.
So, where do we go from here?
One ripe area for investment is supply chain management. Companies like Amazon, UPS, and DHL already leverage AI-powered systems to optimize their supply chains, improve delivery times, and reduce costs. At AlixPartners, we have developed a Global Trade Optimizer tool that assesses a company’s entire supply chain, identifies critical vulnerabilities, and employs predictive modeling and monitoring to address the identified risks. Amid recent disruptions to supply chains, these capabilities have never been more critical.
Customer service is another domain that often leaves companies and their customers dissatisfied. While many organizations hesitate to replace call centers with generative AI-driven chat interfaces, features like co-pilots, which equip call center operators with LLMs to answer queries and enhance productivity, show great promise. Beyond call centers, HSBC is utilizing a similar AI tool to streamline services and optimize pricing.
Generative AI is also revolutionizing customer relationship management databases by unlocking previously siloed information. These technologies enable quick access to knowledge, skillsets, and organizational experience. They can also facilitate mapping client relationships and networks of influence, potentially transforming sales and marketing strategies.
AI can go beyond a mere piece of IT infrastructure. It has the potential to become a valuable collaborator within your workforce, whether you’re serving customers, managing supply chains, or juggling myriad other tasks. As my colleagues Angela Zutavern and Ted Bililies recently emphasized, the true power of technology, specifically AI, lies not in replacing human labor but in collaborating with it. As the world becomes increasingly complex, dynamic, and unpredictable, adapting quickly and making informed decisions based on ever-growing data becomes imperative. AI tools can provide invaluable assistance in making these decisions. However, it is crucial to remember that the application of human wisdom and judgment remains paramount.
With all the hype surrounding generative AI, artificial intelligence has experienced its own moment akin to Netscape’s impact on the internet. Just as the Netscape browser enabled average individuals to grasp the internet’s potential, chat tools in the AI realm allow us to witness the tremendous progress made in this field.
Now, the challenge for all of us lies in deploying these new technologies ethically and securely while identifying the suitable use cases for investments.
Continue reading about AlixPartners’ strategic partnership with the AI software company NAX here.
Originally published on June 2, 2023.
