The Generative AI Revolution: Takers, Shapers, and Makers

Imagine a future where AI writes captivating marketing copy, designs innovative products, and composes original music. This is the power of Generative AI (#GenAI). From creating personalized marketing campaigns that boost ROI by 20% to accelerating drug discovery.

Gen AI holds immense potential. For example, Google found that of firms who implemented generative AI 45% reported a doubling of employee productivity and 63% saw #GenAI directly fuel business growth.

Yet, many businesses remain hesitant to adopt it due to fear or ignorance. While understandable, these cannot be reasons businesses miss out on the most transformative technology since the World Wide Web. The truth is that every business has a role in the Generative AI ecosystem, regardless of size or budget.

The Rapidly Evolving Generative AI Landscape

Fuelled by advances in deep learning expertise and natural language processing computing power, Gen AI is making huge strides. Gen AI tools can generate realistic images, translate languages, and write creative content and computer code with near-perfect accuracy.  

Take, for instance, Microsoft's CoPilot, an AI-powered intelligence assistant that assists programmers in boosting productivity, code quality and document by providing context-aware code completions, suggestions, and even entire code snippets. It's like having a pair programmer who can help you write and debug your code, generate your unit tests and more. Amazon's Code Whisperer and GitHub CoPilot are somewhat similar AI services. These are just a few examples of the powerful Gen AI tools that businesses can leverage. 

Gen AI Takers: Extracting Immediate Value 

A Gen AI Taker uses readily available public SaaS LLM (Large Language Model) services through APIs (Application Programming Interfaces) or chat interfaces, such as those provided by OpenAI and Microsoft Azure OpenAI, without any customization. These tools help streamline business operations and enhance productivity, creativity, and overall work quality. It's the easiest and fastest entry point into the Gen AI world. Businesses can leverage these tools to:

• Creativity: Imagine designers or marketing teams using Adobe Firefly to generate and edit images or Anthropic's Claude.ai Gen AI to create personalized emails or social media content at scale, freeing valuable time for more strategic action. 

·      Boost Your Productivity with Generative AI (hbr.org)

• Answers Customer Queries 24/7: Customer service chatbots powered by Gen AI can handle customer inquiries intelligently and in a human-like way, freeing human agents to focus on complex customer issues. For example, Salesforce Einstein GPT, its GenAI chatbot, uses LLMs to improve its customer relationship management (CRM) software. Einstein GPT enables customers to connect their data to OpenAI's models to generate content, schedule meetings, write emails, and gather pre-call customer context that dynamically adapts to changing customer information.

·      Wakening up hibernating RPA robots (Kieran Gilmurray)

• Fuel Innovation: Design teams can utilize Gen AI tools such as Midjourney, Synthesia, or DALL-E to generate a wider range of creative concepts, leading to a more innovative product development process.

·      Generative AI fuels creative physical product design but is no magic wand | McKinsey 

• Automate Processes: Studies by McKinsey & Company show that businesses embracing automation technologies like Gen AI and Large Action Models can deliver a productivity boost of up to 25%. For example, Zapier, a company specializing in workflow automation, utilizes Gen AI to help users discover relevant automation opportunities that help to streamline their processes significantly.

·      AI at Zapier: How we use artificial intelligence to streamline work

Gen AI Maker: Integrating and Customizing AI for Unique Advantage 

Gen AI Makers take the next step by integrating off-the-shelf Gen AI models with their data to create custom solutions tailored to their business needs. For example, platforms like Amazon's Bedrock or Druid AI enable businesses to fine-tune pre-trained AI models with their unique datasets. This enables them to:

• Rapidly Solve Industry-Specific Problems: For example, a financial services company might train a Gen AI model to analyze historical financial data more effectively than a human to identify fraud patterns.

·       Which Problems Are Enterprises Trying to Solve With Generative AI? (forbes.com)

• Develop a Competitive Edge: A retailer might personalize product recommendations based on a customer's past purchases and browsing behaviour, which would increase sales and customer satisfaction.

·       Turn Generative AI from an Existential Threat into a Competitive Advantage (hbr.org)

·       Instacart Harnesses Generative AI To Revolutionize Grocery Delivery Experience

• Accelerate Drug Discovery: the pharmaceutical giant Genentech utilizes Gen AI to analyze vast amounts of scientific data, accelerating drug discovery and development. This highlights the strategic advantage Makers gain competitive advantage by customizing Gen AI, using their data and online GenAI platforms, to deliver their specific business goals.

Gen AI Shaper: Pioneering for Strategic Dominance

Gen AI Shapers are the true vanguards of the AI revolution. They build private, secure, Large and Small Language Models (LLMs and SLMs), such as OpenAI, Microsoft Azure private cloud, and tailor them using their IP for their specific business needs to gain a competitive edge. 

 ·   OpenAI. OpenAI developed the advanced GPT-4.o and DALL-E 3—two of today's most powerful GenAI models. 

·    Google AI. Google AI developed the transformer model, the foundation for many of the most popular GenAI models today. Google has two LLMs: PaLM (multimodal model) and Gemini (pure language model). 

The shaper path is complex, expensive, and resource-intensive but offers a huge competitive advantage for businesses with deep enough pockets. Building and maintaining private LLMs requires a significant investment in data science expertise, computational power, and ongoing training data. This makes it an option currently limited to large organizations such as Microsoft, Google, IBM, EY, and Deloitte.

·      Three Challenges with Adopting Domain-Specific LLMs (forbes.com)

·      IBM breakthroughs could help bring AI training from cloud to edge | IBM Research Blog

Overcoming Challenges and Embracing GenAI Opportunities

Fear of data loss, copywriting theft, high costs, and the unknown can be barriers to adopting Generative AI. However, there are strategies to manage these challenges:

• Phased Investment: Businesses can start small by adopting existing Gen AI tools and gradually increase their involvement as they gain expertise and confidence.

·      2024 Generative AI Planning: How are IT Organizations Preparing? | Gartner

·      How to prepare your organization for AI | McKinsey

• Partnerships: Collaboration with AI consultancies or research institutions can provide access to the expertise and resources needed for Gen AI adoption.
• Staying Informed: Following industry trends and developments closely can help businesses make informed decisions about their Gen AI strategy. 

Regardless of size or industry, every business can benefit from a proactive approach to Generative AI.

How to Get Started on Your Gen AI Journey

To start your generative AI journey, businesses must first assess their current capabilities, needs, business and strategic goals.

• Identify Needs: Is there a repetitive task Gen AI can automate, like scheduling social media posts or generating basic reports? Do you need help brainstorming creative product ideas or writing different marketing content? Pinpointing specific business areas for improvement, innovation, or opportunity will guide your choice between being a Taker, a Shaper, or a Maker.
• Are there existing GenAI platforms or tools available, or do you need to create them? The Gen AI landscape is vast. Numerous online resources showcase existing Gen AI tools and APIs, categorized by function and industry. Look for solutions that align with your identified needs, your budget, and your access to expertise.
• Consider Partnerships: For businesses aiming to become Shapers or Makers, explore collaboration with AI consultancies or universities. Their expertise can bridge the gap between your in-house capabilities and your Gen AI ambitions. These partnerships can provide access to cutting-edge research, specialized talent, and the computational resources required for more complex Gen AI projects.
• Stay Updated: The field of Gen AI is constantly evolving. Subscribe to industry publications like MIT Technology Review or AI News, attend relevant conferences like AAAI, and participate in online communities to stay abreast of the latest developments. This will help you identify new tools and strategies to maximize your Gen AI ROI.

Should you be a taker, maker, or shaper?

The cost of acquiring and developing GenAI solutions can range from next to nothing to millions of dollars, depending on the specific use case and scale of the business problem[1].  

So, if you are a newcomer organization aiming to venture into generative AI, utilizing such open platforms could be a prudent starting point. Publicly available generative AI applications like Claude, Gemini, DALL-E or ChatGPT offer a cost-effective solution for small and medium-sized enterprises seeking to address routine and straightforward business operational challenges. 

·      Claude

·      Google Gemini

·      Salesforce Launches Einstein 1 Studio: Low-Code AI Tools for Customizing Einstein Copilot and Embedding AI into Any CRM App - Salesforce

Organizations reluctant to openly entrust their valuable data to external entities may opt for a secure platform generative AI solution such as Amazon Bedrock or Azure OpenAI, which is capable of addressing complex operational security and privacy challenges. Such an approach ensures adherence to governance and ethical standards while maintaining control over sensitive information without the expense of building a bespoke LLM or SLM.

·      Build Generative AI Applications with Foundation Models - Amazon Bedrock - AWS

·      Microsoft Azure

Large organizations like IBM, Deloitte, EY, Salesforce, or Accenture that supply services to others or possess unique IP or domain-specific knowledge that offers significant competitive advantage that they do not wish to be exposed to others where they need predictability and accuracy in output are more likely to be shakers. 

·      EY announces launch of artificial intelligence platform EY.ai following US$1.4b investment | EY - Global 

A Generative AI Infused Future is Now

The potential of Generative AI to transform industries is undeniable with 74% of businesses already seeing returns on their #GenAI investments. Businesses that hesitate and sit on the side-lines risk falling behind their competitors (i.e., AI Darwinism). By embracing the role of Taker, Maker, and Shaper, companies of all sizes can unlock the value of Gen AI and gain a competitive edge based on their unique needs.

The question isn't if you'll use Gen AI, but how. This is a journey that you don't have to go through alone. I can help you assess your options and navigate the exciting world of Generative AI. 

Let's discuss your specific needs and chart a course to unlock the value of Gen AI for your business. Whether you're a small start-up or a large enterprise, a Gen AI path is waiting to be explored. Take the first step today and see how Gen AI can revolutionize your business by contacting me.

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Research Source:  [1] Demystifying The GenAI Marketscape: Shakers, Makers And Takers (forbes.com)

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