Global Generative AI in Sales Market By Industry (Retail, Healthcare, and Others), By Deployment (On-premises, Cloud-based, and Hybrid), By Application (Customer Profiling, Lead Generation, and Others), By Functionality (Natural Language Processing, Deep Learning, and Machine Learning), By Region and Companies - Industry Segment Outlook, Market Assessment, Competition Scenario, Trends, and Forecast 2023-2032

Report Overview

Global Generative AI in sales Market size is expected to be worth around USD 769.8 Mn by 2032 from USD 279.5 Mn in 2022, growing at a CAGR of 10.9%. during the forecast period from 2023 to 2032.

The Generative AI in sales Market that is rapidly growing. This is due to the increasing adoption of AI sales solutions by companies to improve their sales productivity, customer engagement, and revenue growth. Generative AI is artificial intelligence that can create content. It is increasingly used in the sales industry to personalize the customer experience, optimize sales campaigns, improve sales forecasting, etc.  These technologies can analyze customer data to generate personalized marketing messages, product recommendations, and sales proposals. The need for sales teams in a highly-competitive market to work more efficiently is another driver. This is driving the adoption of AI-powered chatbots and sales automation tools.

Global Generative AI in Sales Market Scope

Industry Analysis

Based on the industry, the generative AI in sales market in sales is segmented into retail, healthcare, finance, and manufacturing. The retail industry is dominant in the market with a market share of 36%. In the retail sector, generative AI is used to create customized sales pitches and recommendations, improve pricing schemes, and examine client data to spot patterns and trends.

Generative AI is being applied in the healthcare sector to personalize patient experiences and enhance results. Generative AI is being used by banks and other financial institutions to analyze client data, give individualized recommendations and offers, and automate sales activities like loan applications and account openings. Manufacturers are utilizing generative AI to analyze sales data, spot trends, and patterns, and create individualized sales pitches and customer suggestions.

Deployment Analysis

By deployment, the generative AI in sales market is divided into on-premises, cloud-based, and hybrid. Among that cloud-based deployment mode is dominant in the market with a share of 49%. The term "cloud-based deployment" describes the use of the cloud to access generative AI systems. Small and medium-sized firms that lack considerable IT infrastructure or resources frequently use this deployment method.

The term "on-premises deployment" describes the installation of generative AI systems at the client's location. Large businesses with extensive IT infrastructure and resources frequently choose this deployment method. A hybrid deployment is a combination of on-premises and cloud-based deployment methods. Businesses that want to gain benefits from both cloud-based and on-premise deployments, can use hybrid deployment mode.

Application Analysis

Based on the applications, the generative AI in sales market is segmented into customer profiling, lead generation, product recommendations, sales forecasting, and campaign optimization. By analyzing consumer data and building thorough profiles of each client that include their tastes, behavior, and past purchases, generative AI is being employed in this process.

Based on a prospect's behavior and interactions with a company's website and other digital channels, generative AI is being used to identify and qualify leads. By analyzing client data and making tailored product recommendations based on their tastes and behavior, generative AI is being employed in this process. To estimate future sales results, generative AI is being used to analyze sales data and find patterns and trends. This aids in the better planning and optimization of sales tactics by sales teams.

Functionality Analysis

Based on the functionality, the generative AI in sales market is segmented into natural language processing, deep learning, and machine learning. The processing and analysis of natural language data, including customer chats, emails, and social media postings is made possible by natural language processing, a vital technology in generative AI systems.

Deep learning is used by generative AI systems to find patterns & relationships in massive datasets, produce forecasts and recommendations and enhance the precision and efficacy of sales processes. Machine learning is used by generative AI systems to automate sales processes, analyze client data, and present tailored recommendations and deals.

Key Market Segments

Based on Industry

• Retail
• Healthcare
• Finance
• Manufacturing

Based on Deployment

• On-premises
• Cloud-based
• Hybrid

Based on  Application

• Customer Profiling
• Lead Generation
• Product Recommendations
• Sales Forecasting
• Campaign Optimization

Based on Functionality

• Natural Language Processing
• Deep Learning
• Machine Learning

Market Dynamics

Drivers

The driving factors for generative AI in sales market include the need for a sales team to work more efficiently and productively, also the emergence of AI-powered chatbots and sales automation tools. The adoption of generative AI technologies, which analyze customer data and provide personalized sales offers, product recommendations, and marketing messages, is being driven by the rising need for personalized customer experiences.

This is in response to shifting consumer expectations and the requirement for companies to stand out in a crowded market. The use of AI-powered chatbots and sales automation systems that can automate tedious processes and give sales teams useful insights into client behavior is another result of the need for sales teams to operate more productively and efficiently.

Finally, as organizations look to strengthen their competitive position and profit from AI technology, the general trend towards digital transformation in the business world is what is driving the adoption of AI-powered sales solutions.

Restraints

The widespread deployment of generative AI in sales market is constrained by a number of factors. The scarcity of data is one of the key restraints, which has an impact on the precision and dependability of generative AI systems. In addition, there are ethical questions about the possible manipulation of customers as well as privacy issues regarding the usage of sensitive customer data.

Implementing generative AI systems in sales processes can be expensive and difficult, and it can also be difficult to customize and understand them. To fully utilize generative AI in sales market, businesses must address these issues.

Opportunity

In the sales business, generative AI technology has a lot of potential. Generating personalized sales presentations and recommendations for customers is one of the key benefits of employing generative AI, which can enhance customer satisfaction and boost sales.

Large volumes of sales data can be analyzed by generative AI to spot patterns and trends, which can assist businesses in making informed decisions about their sales strategy. Additionally, generative AI may automate sales procedures like lead qualifying and scoring, freeing up sales representatives to concentrate on forging connections with clients.

Additionally, generative AI can help with consumer behavior forecasting and the detection of possible upsell and cross-sell opportunities. As generative AI technology develops further, there might be even more prospects for its use in the sales industry, such as in chatbots and virtual sales assistants. In conclusion, there are a lot of prospects for generative AI in the sales sector, which might lead to better sales outcomes, greater efficiency, and better customer experiences.

Trends

The generative AI in sales market is growing rapidly. Several trends are driving its growth. The adoption of generative AI by the sales industry is one of the most notable trends, largely due to technological advancements and the availability of more data.

Another trend is to use generative AI for personalized sales pitches and suggestions, which can improve sales strategies. In addition, generative AI can be used to automate processes such as lead scoring and qualification and to analyze large amounts of data to identify patterns and trends.

The trend in the market is the integration of AI with other technologies such as chatbots & virtual assistance. As technology advances, generative AI may have more applications in sales. For example, predictive lead scoring and sales analytics. The trend of increased adoption and integration in the sales industry will continue to grow, driven by a desire to improve customer experiences and sales outcomes.

COVID-19 Impact Analysis

The COVID-19 pandemic has significantly impacted several other industries as well as the global market for generative AI in sales. As businesses had to adjust to remote work and e-commerce during the pandemic, one of the biggest effects was the acceleration of generative AI technology adoption.

Due to this, generative AI is now being used more frequently to personalize consumer experiences in virtual environments and automate sales procedures like lead scoring and qualifying. The rising use of generative AI for predictive sales analytics as firms need to make data-driven decisions in a fast-changing environment is another effect of the pandemic. In order to help firms adjust their sales tactics to shifting market conditions, generative AI can analyze massive volumes of sales data to detect patterns and trends.

The pandemic has also underlined the value of delivering individualized customer experiences as companies work to forge lasting bonds with clients in a remote settings. With the use of generative AI technology, organizations can create personalized sales pitches and customer suggestions that can strengthen customer connections and boost sales.

The epidemic has, however, also presented some difficulties for the sales market's generative AI. For instance, because of changes in consumer behavior during the epidemic, firms may experience difficulties accessing the necessary data. Additionally, as they deal with the pandemic's economic effects, businesses can run into financial difficulties.

Regional Analysis

North America is the region with the largest market for generative AI in terms of revenue. North America has a 42% market share. Due to the prevalence of top technological businesses and the rapid uptake of cutting-edge technologies, Due to the existence of top IT giants like Google and Microsoft as well as the extensive use of e-commerce in the US, the country is a significant market for generative AI sales.

Due to the growing commercial use of cutting-edge technology, Europe is another important market for generative AI sales. Due to the existence of top technological businesses and the high levels of digitization in these nations, the United Kingdom, Germany, and France are the three biggest markets for generative AI sales in Europe.

Asia Pacific is the fastest growing for generative AI in sales market, driven by the region's companies' rising reliance on e-commerce and cutting-edge technology. Due to their vast populations & significant growth potential, China, Japan, and India are the three nations with the highest sales of generative AI in the Asia Pacific region.

In the Latin America region due to the growing use of cutting-edge technology, the market starts to expand. The market for generative AI in sales is also in its introduction phase in the regions such as the Middle East and Africa. In the upcoming years, generative AI in sales is anticipated to be driven by the expansion of the e-commerce sector in these regions.

Key Regions

• North America
  • The US
  • Canada
  • Mexico
• Western Europe
  • Germany
  • France
  • The UK
  • Spain
  • Italy
  • Portugal
  • Ireland
  • Austria
  • Switzerland
  • Benelux
  • Nordic
  • Rest of Western Europe
• Eastern Europe
  • Russia
  • Poland
  • The Czech Republic
  • Greece
  • Rest of Eastern Europe
• APAC
  • China
  • Japan
  • South Korea
  • India
  • Australia & New Zealand
  • Indonesia
  • Malaysia
  • Philippines
  • Singapore
  • Thailand
  • Vietnam
  • Rest of APAC
• Latin America
  • Brazil
  • Colombia
  • Chile
  • Argentina
  • Costa Rica
  • Rest of Latin America
• Middle East & Africa
  • Algeria
  • Egypt
  • Israel
  • Kuwait
  • Nigeria
  • Saudi Arabia
  • South Africa
  • Turkey
  • United Arab Emirates
  • Rest of MEA

Market Share & Key Players Analysis

The global generative AI in sales market is highly competitive, with several key players operating in the market. These companies are primarily focused on developing and offering generative AI solutions for sales processes, such as lead scoring, customer segmentation, and personalized recommendations. They are also investing in research and development to improve the accuracy and effectiveness of generative AI in sales.

In terms of market share, specific figures can vary depending on the source and methodology used. However, some reports suggest that IBM Corporation, Google LLC, and Salesforce.com, Inc. are among the leading players in the generative AI sales market, with significant market shares. These companies have established strong brand recognition & have developed advanced generative AI solutions for sales processes.

Listed below are some of the most prominent generative ai in sales industry players.

Market Key Players

• Salesforce
• IBM
• Adobe
• Oracle
• Conversica
• Gong
• InsideSales
• XANT
• Other Key Players

Recent Developments

• In January 2021: IBM announced the launch of its AI-powered sales solution, IBM Watson Sales Manager, designed to help sales teams improve their performance and effectiveness.
• In July 2020: Salesforce announced the acquisition of Vlocity, a leading provider of industry-specific cloud and mobile software, to expand its offerings in the generative AI in sales market.

Report Scope