What areas will be further disrupted by Generative AI in 2024?
75% of people that use Generative AI are looking to automate tasks and communication at work.
Marketing and sales, product and service development, and service operations, such as customer care and back-office support are business functions that use generative AI most extensively.
Yes. We are already in the middle of a revolution. Generative AI is a game-changer. The integration of AI into these critical business areas is reshaping how companies approach their strategies and operations. It was so already in 2023 and will continue in 2024. If you are not on board, you will be outside very soon.
Generative AI in Marketing and Sales 2024
In 2024, the biggest pain point in marketing and sales for generative AI likely centers around the balance between personalization and privacy. Here are some key aspects of this challenge:
In the marketing and sales sector, generative AI has transitioned from a futuristic concept to practical and indispensable tool. Its applications range from drafting text documents to personalizing marketing strategies.
With a notable prevalence in crafting initial drafts and comparable usage in personalized marketing and text summarization, AI is proving to be an indispensable asset.
Use cases
Content Creation
Apps leveraging generative AI can produce highly personalized marketing content, including emails, blog posts, and social media posts, tailored to the specific interests and behaviors of individual customers. This enhances engagement and conversion rates.
Video Production
Generative AI tools are capable of creating promotional videos by just inputting a script or a set of instructions. This significantly reduces the time and cost associated with video production, allowing for more dynamic marketing campaigns.
Product Visualization
AI can generate realistic images and 3D models of products in various configurations and environments. This is especially useful for e-commerce, where customers can see customized product renderings based on their preferences or past behavior.
Customer Service and Sales
Advanced AI chatbots can handle customer inquiries, provide product recommendations, and even close sales, offering a 24/7 service that can significantly enhance customer experience and operational efficiency.
Market Analysis and Forecasting
AI applications can analyze vast amounts of market data to identify trends, predict future market movements, and provide insights for strategic planning. This includes sentiment analysis on social media to gauge brand perception.
Marketing
Tools that can generate human-like voiceovers for marketing materials, allowing for more personalized and varied audio content in marketing campaigns.
SEO and Content Creation
AI tools that analyze search engine algorithms and user behavior to suggest content changes or create content that is more likely to rank high on search engine results pages.
Email Campaigns
Inbound and outbound marketing campaigns frequently require employees to send contextualized emails and chat threads to prospective and current customers on a daily basis. Generative AI solutions can create and send the content for these communications to lessen the load. In some cases, they can also automate the process of moving these contacts to the next stage of the customer lifecycle on a CRM platform.
These types of assistive generative AI tools are increasingly popping up in both CRM and project management platforms, but there are also many independent generative AI tools for sales and marketing workflows. If your team of sales development representatives, marketers, salespeople, or other members who focus on outreach are getting minimal results with their current outreach strategies, the right tool can help them generate better content at a greater scale. Even better, a growing number of these sales and marketing tools include AI-powered analytics so you can develop a deeper understanding of what is and isn’t working with your current tactics.
HubSpot’s generative AI tools are currently in public beta; with this particular feature, users can provide the tool with minimal information so HubSpot can generate relevant outreach emails. Source: HubSpot.
Example solutions
Twain
Salesforce Einstein GPT
HubSpot AI
Examples of custom prompts
- “Write a minute-long advertisement script about [product, service, or company].”
- “Create a 3-month social media campaign calendar for our product with the goal to [insert goal] and mention the channels we should focus on.”
- “Create 3 call-to-action button ideas based on the contents of this blog post URL.” Then insert the URL.
- “Create an advertising campaign about [company, product, or service] targeting [target audience]. Include key messages and slogans and choose the best media channels for promotions.”
- “List the key marketing segments in [industry]. Which segment has the biggest opportunity for our [company, group, organization, business]?”
- “What are 10 main points that are crucial to marketers trying to acquire new customers?”
This technology empowers marketers to generate high-quality content tailored to specific target audiences, leading to more effective and efficient campaigns. You still can do your GTM campaign manually, but it might take longer and less effective as your competitor will do.
Generative AI in Product and Service Development 2024
In 2024, the biggest pain point in using generative AI for product and service development is likely the challenge of ensuring the alignment of AI-generated solutions with actual user needs and market demands. This encompasses several key aspects:
The influence of generative AI extends to product and service development, where understanding customer needs is paramount.
AI plays a pivotal role in identifying trends in customer preferences, drafting technical documents, innovating new product designs, staying ahead of market demands, and fostering innovation.
Use cases
Rapid Prototyping
AI tools can generate multiple design prototypes for products based on specified parameters or design goals. This accelerates the design process and allows for exploration of more creative and diverse design options.
Customization and Personalization
AI systems can generate customized product designs or configurations based on individual customer preferences or needs. This is particularly useful in industries like fashion, automotive, and consumer electronics.
AI-Driven Simulation and Testing
Before a product is physically built, generative AI can simulate how it will perform under various conditions, reducing the time and resources spent on physical testing.
Material Innovation
AI can help in discovering new materials or material compositions by predicting properties and performance, leading to the development of innovative products with enhanced features.
User Experience Design
For digital products and services, generative AI can help create more intuitive and user-friendly interfaces and experiences by analyzing user interaction data and generating design improvements.
Predictive Maintenance in Product Lifecycle
AI can predict when parts of a product are likely to fail or need maintenance, helping in designing products that are easier to maintain and have longer lifespans.
Sustainable Product Development
Generative AI can be utilized to design products and services that are more environmentally sustainable, by optimizing for factors like energy efficiency, recyclability, and minimal waste.
Product Design Optimization
Using generative AI, companies can optimize product designs for functionality, aesthetics, or resource efficiency. The AI can iterate through countless designs, considering factors like material costs, durability, and environmental impact. Companies such as Autodesk use AI to assist in product design. Their tool, Dreamcatcher, uses AI to generate design options based on the designer’s requirements.
Custom Software Engineering
Generative AI can also be used in software engineering to automate the creation of custom software. GPT-3, for example, can generate code based on natural language descriptions.
The latest research focuses on improving code generation accuracy and efficiency. For instance, researchers are developing AI models to better understand the code’s context and generate more accurate and efficient code. Companies such as GitHub are using AI to assist developers in writing code. Their tool, Copilot, uses GPT-3 to suggest code snippets to developers.
Leading manufacturers are hitting the ground running with gen AI.
Global airline supplier, GA Telesis, has integrated Google Cloud’s gen AI technology to revolutionize sales processes. CEO Abdol Moabery said, “In aerospace, GA Telesis will deploy Google Cloud’s generative AI technology to revolutionize the sales and service processes for the parts the company supplies to major global passenger and cargo carriers.”
US Steel is building applications using Google Cloud’s generative artificial intelligence technology to drive efficiencies and improve employee experiences in the largest iron ore mine in North America.
“We’ve meaningfully accelerated digitization at U. S. Steel through our work with Google Cloud. Faster repair times, less down time, and more satisfying work for our techs are only some of the many benefits we expect with generative AI,” said David Burritt, president and CEO of U. S. Steel. “I’m thrilled that the U. S. Steel team is a manufacturing leader in this work.”GE Appliances helps consumers create personalized recipes from the food in their kitchen with gen AI to enhance and personalize consumer experiences. GE Appliances’ SmartHQ consumer app will use Google Cloud’s gen AI platform, Vertex AI, to offer users the ability to generate custom recipes based on the food in their kitchen with its new feature called Flavorly™ AI. SmartHQ Assistant, a conversational AI interface, will also use Google Cloud’s gen AI to answer questions about the use and care of connected appliances in the home.
Generative AI in Service Operations 2024
In 2024, the biggest pain point in applying generative AI to service operations is likely the challenge of achieving optimal human-AI collaboration. This issue encompasses several key aspects:
| Integration | Quality and Consistency | Balance |
| Seamlessly integrating AI into existing service operation workflows can be complex. There’s often a significant gap between AI capabilities and existing operational infrastructure, leading to potential disruptions or underutilization of AI. | Ensuring that the outputs generated by AI are consistently high-quality and reliable is crucial. In service operations, any inaccuracy or inconsistency in AI-generated responses or actions can significantly impact customer satisfaction and operational efficiency. | Finding the right balance between automated AI solutions and human judgment is challenging. Over-reliance on AI can lead to impersonal or inadequate service experiences, while underutilization can result in missed opportunities for efficiency and improved service quality. |
In the realm of service operations, generative AI is making significant strides, revolutionizing processes and enhancing overall efficiency. Chatbots are increasingly utilized in customer service, alongside AI’s growing role in forecasting service trends and anomalies, and creating document drafts, thereby enhancing efficiency and predictive capabilities.
List of enterprise applications that already integrated GenAI and Chatbots.
Salesforce Einstein
Salesforce’s AI platform, Einstein, integrates generative AI for predictive analytics, customer insights, and personalized customer interactions. It also features advanced chatbot capabilities for customer service and sales automation.
Microsoft Dynamics 365 AI
This suite of enterprise applications includes AI-driven insights and chatbot solutions, enhancing customer service, sales, and marketing operations with predictive analytics and automated customer engagement.
IBM Watson Assistant
IBM’s AI assistant offers advanced chatbot functionalities integrated with its enterprise solutions. It’s used in various sectors for automating customer support, internal operations, and providing personalized user experiences.
SAP Conversational AI
SAP’s chatbot and AI capabilities are integrated into its enterprise resource planning (ERP) and customer relationship management (CRM) systems, offering automated customer service and operational efficiency.
Oracle AI
Oracle integrates generative AI and chatbots across its cloud applications, including ERP, CRM, and Human Capital Management (HCM), to provide intelligent automation and real-time insights.
Zendesk Answer Bot
Integrated within Zendesk’s customer service platform, this bot uses AI to understand customer queries and provide instant, accurate responses, improving resolution times and customer satisfaction.
ServiceNow’s Now Assist
This AI-powered chatbot is designed to automate routine tasks in IT service management, customer service, and employee workflows, enhancing overall service operations.
Adobe Sensei
Integrated within Adobe’s Creative Cloud and Experience Cloud, Adobe Sensei uses AI and machine learning for content personalization, marketing automation, and customer analytics.
HubSpot’s Chatbot Builder
Part of HubSpot’s CRM platform, this tool allows businesses to create custom chatbots for lead generation, customer support, and automating interactions, integrated seamlessly with sales and marketing tools.
Pega AI and Decisioning
Pegasystems offers AI-driven decisioning and workflow automation capabilities, which include chatbot functionalities to improve customer engagement and operational processes.
Freshworks AI Chatbots
Integrated within Freshdesk and Freshsales, these AI chatbots offer automated customer support, lead qualification, and sales engagement.
Intercom’s Resolution Bot
This chatbot is designed for automated customer support and engagement, integrated with Intercom’s messaging platform.
We developed an extension for ServiceNow platform that enables service owners and operations managers to speedup and automate steps in their processes. By integrating small AI assistants into your customer support, employee and legal operations, security and risk management, you can remove repetitive work and let your agents focus on really relevant things.
Business Impact of Generative AI in 2024
A research by Mckinsey finds out that generative AI could add the equivalent of $2.6 trillion to $4.4 trillion. annually across the 63 use cases we analyzed—by comparison, the United Kingdom’s entire GDP in 2021 was $3.1 trillion. This would increase the impact of all artificial intelligence by 15% to 40%.
It underscores the critical role of generative AI in modern business operations. Its ability to dynamically target audiences, automate tasks, and personalize marketing strategies not only enhances productivity but also streamlines processes. These AI-driven techniques enable businesses to allocate their time and budget more effectively, thereby maximizing their return on investment.
Conclusion
The multifaceted applications of generative AI in 2023 reshaped the landscape of business operations, spanning marketing, sales, product development, and service operations.
Companies can thrive in the digital age by leveraging AI for personalized marketing, innovative content generation, and increased productivity.
How is your organization leveraging generative AI to stay ahead in today’s competitive market? If you are still looking for applicable use cases or the ways to integrate AI into your workflows and operations, get in touch with us.
Teiva Systems is a ServiceNow Premier Partner and provides advisory, architecture, implementation, training and support services. Teiva Systems specializes in building custom applications and integrations with App Engine Studio and Platform Intelligence considering common data model, security, business intelligence, machine learning, integration layer across various industries and regions, especially USA, Germany, Switzerland, Austria, Lithuania, Ukraine.
Kostya Bazanov is ServiceNow Leading Architect and Technology Advisor since 2011. He acted in various roles such as technical consultant, implementer, solution architect, team lead in national and global projects and ServiceNow platform rollouts. Kostya is certified in ServiceNow service management, operations management, custom applications.
Kostya Bazanov, Managing Director, Jan 31, 2024
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