In our earlier post we evaluated pros & cons of GPT Chat….if not read it pls refer…. before getting down to conclusive outcomes.
Read more: GPT Chat : So, what is it useful for?Conclusions:
This new class of Transformer-based models has the potential to significantly accelerate enterprise AI adoption without requiring extensive AI or data science expertise. Additionally, this technology has the potential to fundamentally alter the human-computer interaction model for enterprise applications.
Given the rate at which technology is advancing, business leaders should expect the technology to be ready for integration into production systems within the next year, implying that the time to begin internal innovation is now. Building Generative AI into products, systems, and processes will necessitate rethinking customer journeys, developing new skills, and managing significant labour changes, all of which will take time for a company to digest. We recommend starting small and early to experiment and gain experience before moving on to more complex, high-impact use cases as the organisation and technology improve and evolve.
Today, a number of early use cases are emerging:
Software development – Microsoft launched its Copilot service on GitHub, which can generate blocks of software code based on natural language instructions, leveraging OpenAI’s model. Development teams that have implemented the technology have reported up to a 55% increase in efficiency.
Productivity and Collaboration – Personal productivity tools such as email or word processing can incorporate AI-enhanced automation of manual processes. Microsoft is incorporating the recently released GPT-3.5 as a component of its premium version of Teams to improve meeting recordings by dividing them into sections, generating titles, adding personalised markers, and highlighting mentions. Startup Jesper.ai offers an AI-powered word processor that generates full text for marketing copy, job descriptions, and a variety of other common writing tasks.
Conversational chatbots for customer service and sales – Chatbots have historically fallen short of expectations. This generation is finally ready for the spotlight. Using a Generative AI chatbot as the first point of contact for web chat and SMS support ensures that customers have no wait time and that most issues can be resolved without escalation to a human, saving significant labour.
Marketing copy generation and optimization – A large part of digital marketing effectiveness is testing and optimising across a large audience. At scale, generative AI can provide an infinite number of subject line and copy variations, increasing marketing efficiency and enabling far better optimization.
Social listening / automated analyst – Generative models are excellent at summarising text and extracting key data and sentiment in social listening and automated analysis. When applied to a social media feed, this can enable detailed social listening for key themes and sentiments about a brand. Alternatively, applying to a feed of public company earnings reports and company news can take the place of junior equity analyst work.
Enterprise search – Enterprise search of internal documents such as research, presentations, or contracts can help a company’s knowledge transfer significantly. Generative AI solutions can securely ingest company documents before answering questions in a summarised manner and highlighting relevant portions of source documents.
Knowledge management – Generative AI models are proving to be effective at condensing lengthy documents and material into concise paragraphs and providing citations to sources. Furthermore, they are now generating content (e.g., analytics with charts and graphs) compiled from various systems of record.
This is only the start.
With Generative AI models only recently entering the digital landscape, we are at the very beginning of developers, entrepreneurs, and corporate innovators figuring out how to apply this technology to high-value use cases. However, as companies, employees, and customers become more familiar with technology-based applications, and as Generative AI models become more capable and versatile, a whole new level of application will emerge.
Some game changers that are likely to become a reality in the next 2-5 years are as follows: “Alexa for work” – Consider a company – wide virtual assistant that, like your home Alexa or Siri assistant, provides a conversational interface for interacting with all internal processes. Employees can chat, email, SMS, or call an agent who can handle a variety of tasks such as HR or vacation requests, financial report generation, IT equipment provisioning, and even career or leadership coaching.
100% AI customer support – Imagine having support available 24 hours a day, seven days a week, and capable of addressing any customer issue in a delightful conversational format indistinguishable from interacting with a human. With instant access to complete product and account information and the ability to trigger actions in systems of record, support quality can be higher than human while incurring no labour costs.
Business analyst with artificial intelligence – Ask your AI analyst natural language questions and it will automatically return insights, graphs, and analysis based on synthesising complex data and producing high-quality narrative output. This will allow for more dynamic leadership decision making by increasing visibility into business performance and drivers.
Outbound selling that is completely automated – The next evolution of outbound selling will be individually personalised email, SMS, or phone outreach with immediate conversational response to customer interest. Sales teams will deploy their Generative AI sales agent across the entire market, generating warm leads for human sellers to close.
Industry sector-specific offerings will emerge quickly, leveraging the power of Generative AI to address their unique challenges and opportunities. Mental-health therapist bots are already proving useful and have the potential to alleviate the severe shortage of mental-health professionals. Artificial intelligence-powered medical diagnostics will spread across medical specialties, improving doctors’ diagnostic accuracy. Based on text commentary, Legal Generative AI engines will generate legal contract revisions. The possibilities are nearly endless.
What was once considered science fiction is now becoming reality right in front of our eyes. With models capable of conversing with humans, following arbitrary conversational instructions, interacting with system-of-record data, and performing any digital task, we should consider Generative AI agents as a new part of the labour force.
They will not replace all labour – “deskless” workers who perform tasks with their hands will be spared for the time being, and many applications will augment rather than replace human productivity. To embed AI into business workflows, business models must be rethought and working methods must be transformed. Companies that do not embrace the resulting disruptive change in labour productivity will be at a potentially catastrophic cost and innovation disadvantage.
It’s time to meet ChatGPT.
