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The rise of Generative Artificial Intelligence (GAI) has transformed the landscape of business, bringing with it a whirlwind of innovation and efficiency. But what are practical ways businesses can harness its potential to boost their return on investment?
In this article, we’ll explain why generative AI has taken the world by storm, discuss the biggest disruptions generative AI brings to business, and share how to apply gen AI to your business in truly transformative ways, using our own real-life examples.
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What is generative AI? A quick video primer:
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When generative AI came into the public consciousness in 2022, most people used it for fun, generating cinematic new profile pictures for themselves or challenging ChatGPT to rewrite the Star Wars script in iambic pentameter. (Note: Did you know the “GPT” in ChatGPT stands for “Generative Pre-trained Transformer?”)
But gen AI’s applications go way beyond personal creative projects, allowing humans and machines to collaborate in whole new ways. A few quick applications of gen AI:
The effect of these applications on a business—any business—can’t be overstated. The impact of generative AI will be comparable to the impact of harnessing electricity—it’s not just a new technology, but a fundamental environmental change and upgrade to the ways in which we work. And organizations that don’t adopt an AI-first mindset are doomed to become obsolete.
Gen AI has sparked a revolution across diverse business landscapes. Three disruptions stand out in their potential to redefine business operations and strategy, no matter what sector you work in.
Initially seen as a tool for developers and data scientists, AI has become accessible to employees across all functions in a business. These days, everyone is an information worker—whether they work with financial reports, sales data, or customers on the floor, understanding and using information makes them more capable at their job. AI-driven tools and platforms can enhance everyone’s productivity significantly.
A couple of examples:
Here at Launch, we helped a Fortune 50 health insurer use AI to capture and validate all the data coming in from medical providers via third-party data providers. Models driven by machine learning increased their provider data accuracy from 29% to 97% and saved them $4 million in the first year. And the team that uses this AI system to do their jobs didn’t have to learn to code!
Essentially, the democratization of AI across business functions gives every person the ability to do more with less. Not only does this foster a culture of innovation and efficiency, it also paves the way to better employee experiences, thanks to less manual labor and more creative, high-value work.
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Gen AI is not just about automating existing processes; it's about reimagining products and services. Consider Tesla, which upended the electric vehicle market by fundamentally rethinking how a car could be built. Rather than a car company, Tesla positioned itself as a software company wrapped in leather seats and sleek paneling, and the auto industry has never been the same.
When AI first entered the business world, it found its place in the accessory game, with companies squeezing injections of AI into existing processes. Canva, for instance, now incorporates AI to provide design suggestions, simplifying graphic design for users with no prior design experience. This is a great example of how AI can be integrated into the core of business offerings. However, the real disruption lies in the transition to AI as an operating system—the technology on which we base all our work.
In the near future, businesses will leverage gen AI to create entirely new product and service experiences. For example, an architecture firm may use AI to generate architectural designs that were previously unimaginable, or a financial institution could use AI to provide third-level-down financial reports to clients in real time.
Something that we’re excited about at Launch is Microsoft Copilot, which could completely transform the way our own team writes business proposals, creates presentations, and more. We have also been working with Microsoft on an even more important use of generative AI: improving employee experience and professional development with Viva Nudge.
This shift from AI as an accessory to AI as an OS is about to empower organizations to push the boundaries of what's possible. The key here is creativity in integration—as gen AI becomes deeply ingrained in business processes, it enables the creation of entirely new product and service offerings that were previously inconceivable.
Gen AI has created a new economic landscape where companies that can effectively apply AI will generate higher perceived value for their products and services. These businesses will not only meet but exceed customer expectations in terms of quality, speed, and personalization. As a result, they will attract more customers, retain them for longer, and enjoy a competitive edge in the market.
Conversely, companies that fail to embrace AI risk falling behind in the race to value. They won’t only miss out on the enhanced productivity and innovation as discussed above; they will also struggle to secure investment, as investors increasingly view AI adoption as a marker of future competitiveness. Everyone is trying to determine how much to spend on AI and where, and the divide between AI adopters and non-adopters will have profound implications for the entire industry ecosystem.
Furthermore, the rise of AI is reshaping compensation structures and creating entirely new job industries. AI experts and data scientists are in high demand, with competitive salaries, while traditionally high-earning roles like software development may be on the downswing. Less technical roles are evolving as being AI-fluent becomes a requirement to remain relevant in the job market. This disruption extends beyond individual companies to impact the broader workforce and education systems, emphasizing the need for continuous learning and adaptation.
For businesses aiming to not just survive but thrive in the coming years, embracing these three disruptions isn't an option—it's an imperative. Ignoring them could mean missed opportunities, inefficiencies, and being left behind in the relentless march of innovation.
While generative AI has vast potential, it’s crucial to use it effectively in order to get meaningful results. This requires a mindset shift: everyone in an organization considering how these new tools can help them change the way they approach their work.
Gen AI allows us to create, plan, and iterate nearly immediately and simultaneously. Rather than crafting an idea, drafting a plan, designing the solution, going through rounds of testing, and launching the product or process, you can jump right into planning, designing, and validating at once. The time that could save a product team is immense.
Here are a few real-life example of ways Launch has helped clients change their Industry 3.0 mindset and implement generative AI for new ways of working:
Microsoft Viva is an employee experience platform built on Microsoft 365 that helps people and teams be their best from wherever they work. Launch is helping the Viva team enrich and “smarten” the Viva reports, including reports on productivity insights and organization networking with Azure OpenAI integration.
Using OpenAI large language models (LLMs), we’ve identified collaboration patterns that impact productivity, workforce effectiveness, and employee engagement, and can generate insights and next best actions for its customers. The reporting process now combines the existing narrative with aggregated and anonymized data points, contrasted with industry benchmarks, to generate AI action items and identify focus areas for senior management.
Our client’s worldwide compensation and incentive group uses various methodologies, including ML models, to set targets for sellers. The process uses hundreds of stored procedures and involves a library of over 70 onboarding and training videos with current or former team members.
Using generative AI, we’re working to get people onboarded and ready to sell more quickly. That includes generating comments and summaries for all stored procedures so that they're easier for employees to familiarize themselves with and refer back to later. We are also working on summarizing all video transcripts, so that team members can find relevant ones and get oriented more quickly.
This healthcare client sought to make the claims and treatment process simpler for their patients, providers, and payers. Launch built a model that automatically generates clinical notes from patient information, extracts key information from the notes, and searches the company’s records for similar patient history. The system uses a model pre-trained on patient histories to summarize findings and use consensus modeling to suggest patient conditions.
A healthcare payer can also use this system when receiving new clinical notes, comparing them against claim histories to detect anything anomalous. With the patient history validated, the payor can quickly pre-authorize treatment based on those suggested patient conditions.
The promise of gen AI is tantalizing. But integrating it effectively into an organization requires experience, strategy, and a deep understanding of both its potential and its pitfalls, including how to govern its use ethically. By applying gen AI thoughtfully and strategically, businesses can unlock its tremendous power and set a course for unprecedented growth and success.
%402x.svg){kind=icon}
The rise of Generative Artificial Intelligence (GAI) has transformed the landscape of business, bringing with it a whirlwind of innovation and efficiency. But what are practical ways businesses can harness its potential to boost their return on investment?
In this article, we’ll explain why generative AI has taken the world by storm, discuss the biggest disruptions generative AI brings to business, and share how to apply gen AI to your business in truly transformative ways, using our own real-life examples.
--
What is generative AI? A quick video primer:
--
When generative AI came into the public consciousness in 2022, most people used it for fun, generating cinematic new profile pictures for themselves or challenging ChatGPT to rewrite the Star Wars script in iambic pentameter. (Note: Did you know the “GPT” in ChatGPT stands for “Generative Pre-trained Transformer?”)
But gen AI’s applications go way beyond personal creative projects, allowing humans and machines to collaborate in whole new ways. A few quick applications of gen AI:
The effect of these applications on a business—any business—can’t be overstated. The impact of generative AI will be comparable to the impact of harnessing electricity—it’s not just a new technology, but a fundamental environmental change and upgrade to the ways in which we work. And organizations that don’t adopt an AI-first mindset are doomed to become obsolete.
Gen AI has sparked a revolution across diverse business landscapes. Three disruptions stand out in their potential to redefine business operations and strategy, no matter what sector you work in.
Initially seen as a tool for developers and data scientists, AI has become accessible to employees across all functions in a business. These days, everyone is an information worker—whether they work with financial reports, sales data, or customers on the floor, understanding and using information makes them more capable at their job. AI-driven tools and platforms can enhance everyone’s productivity significantly.
A couple of examples:
Here at Launch, we helped a Fortune 50 health insurer use AI to capture and validate all the data coming in from medical providers via third-party data providers. Models driven by machine learning increased their provider data accuracy from 29% to 97% and saved them $4 million in the first year. And the team that uses this AI system to do their jobs didn’t have to learn to code!
Essentially, the democratization of AI across business functions gives every person the ability to do more with less. Not only does this foster a culture of innovation and efficiency, it also paves the way to better employee experiences, thanks to less manual labor and more creative, high-value work.
Gen AI is not just about automating existing processes; it's about reimagining products and services. Consider Tesla, which upended the electric vehicle market by fundamentally rethinking how a car could be built. Rather than a car company, Tesla positioned itself as a software company wrapped in leather seats and sleek paneling, and the auto industry has never been the same.
When AI first entered the business world, it found its place in the accessory game, with companies squeezing injections of AI into existing processes. Canva, for instance, now incorporates AI to provide design suggestions, simplifying graphic design for users with no prior design experience. This is a great example of how AI can be integrated into the core of business offerings. However, the real disruption lies in the transition to AI as an operating system—the technology on which we base all our work.
In the near future, businesses will leverage gen AI to create entirely new product and service experiences. For example, an architecture firm may use AI to generate architectural designs that were previously unimaginable, or a financial institution could use AI to provide third-level-down financial reports to clients in real time.
Something that we’re excited about at Launch is Microsoft Copilot, which could completely transform the way our own team writes business proposals, creates presentations, and more. We have also been working with Microsoft on an even more important use of generative AI: improving employee experience and professional development with Viva Nudge.
This shift from AI as an accessory to AI as an OS is about to empower organizations to push the boundaries of what's possible. The key here is creativity in integration—as gen AI becomes deeply ingrained in business processes, it enables the creation of entirely new product and service offerings that were previously inconceivable.
Gen AI has created a new economic landscape where companies that can effectively apply AI will generate higher perceived value for their products and services. These businesses will not only meet but exceed customer expectations in terms of quality, speed, and personalization. As a result, they will attract more customers, retain them for longer, and enjoy a competitive edge in the market.
Conversely, companies that fail to embrace AI risk falling behind in the race to value. They won’t only miss out on the enhanced productivity and innovation as discussed above; they will also struggle to secure investment, as investors increasingly view AI adoption as a marker of future competitiveness. Everyone is trying to determine how much to spend on AI and where, and the divide between AI adopters and non-adopters will have profound implications for the entire industry ecosystem.
Furthermore, the rise of AI is reshaping compensation structures and creating entirely new job industries. AI experts and data scientists are in high demand, with competitive salaries, while traditionally high-earning roles like software development may be on the downswing. Less technical roles are evolving as being AI-fluent becomes a requirement to remain relevant in the job market. This disruption extends beyond individual companies to impact the broader workforce and education systems, emphasizing the need for continuous learning and adaptation.
For businesses aiming to not just survive but thrive in the coming years, embracing these three disruptions isn't an option—it's an imperative. Ignoring them could mean missed opportunities, inefficiencies, and being left behind in the relentless march of innovation.
While generative AI has vast potential, it’s crucial to use it effectively in order to get meaningful results. This requires a mindset shift: everyone in an organization considering how these new tools can help them change the way they approach their work.
Gen AI allows us to create, plan, and iterate nearly immediately and simultaneously. Rather than crafting an idea, drafting a plan, designing the solution, going through rounds of testing, and launching the product or process, you can jump right into planning, designing, and validating at once. The time that could save a product team is immense.
Here are a few real-life example of ways Launch has helped clients change their Industry 3.0 mindset and implement generative AI for new ways of working:
Microsoft Viva is an employee experience platform built on Microsoft 365 that helps people and teams be their best from wherever they work. Launch is helping the Viva team enrich and “smarten” the Viva reports, including reports on productivity insights and organization networking with Azure OpenAI integration.
Using OpenAI large language models (LLMs), we’ve identified collaboration patterns that impact productivity, workforce effectiveness, and employee engagement, and can generate insights and next best actions for its customers. The reporting process now combines the existing narrative with aggregated and anonymized data points, contrasted with industry benchmarks, to generate AI action items and identify focus areas for senior management.
Our client’s worldwide compensation and incentive group uses various methodologies, including ML models, to set targets for sellers. The process uses hundreds of stored procedures and involves a library of over 70 onboarding and training videos with current or former team members.
Using generative AI, we’re working to get people onboarded and ready to sell more quickly. That includes generating comments and summaries for all stored procedures so that they're easier for employees to familiarize themselves with and refer back to later. We are also working on summarizing all video transcripts, so that team members can find relevant ones and get oriented more quickly.
This healthcare client sought to make the claims and treatment process simpler for their patients, providers, and payers. Launch built a model that automatically generates clinical notes from patient information, extracts key information from the notes, and searches the company’s records for similar patient history. The system uses a model pre-trained on patient histories to summarize findings and use consensus modeling to suggest patient conditions.
A healthcare payer can also use this system when receiving new clinical notes, comparing them against claim histories to detect anything anomalous. With the patient history validated, the payor can quickly pre-authorize treatment based on those suggested patient conditions.
The promise of gen AI is tantalizing. But integrating it effectively into an organization requires experience, strategy, and a deep understanding of both its potential and its pitfalls, including how to govern its use ethically. By applying gen AI thoughtfully and strategically, businesses can unlock its tremendous power and set a course for unprecedented growth and success.
