This article is an extension of our previous piece, delving deeper into the expanding domain of Generative AI applications within enterprise businesses.
The demand for AI solutions is on the rise as mid-size and larger enterprise businesses recognise the need for specialised applications tailored to their specific requirements. To give an idea of how significant the impact and opportunity could be, consider the Bessemer Cloud Index, a benchmark for enterprise SaaS companies with a market cap of around $1.5 trillion. A mere 10% value addition from AI could present a staggering $150 billion into these companies. With the application of embedded AI into SMEs, the potential value-add could be up to 2-3x that amount ($500bn+).
Adapting generative AI for business use is a complex task that often requires the expertise of enterprise-grade tech companies. These companies possess the skills to integrate AI with existing systems, handle specialised data, and provide essential information and analysis. Virtually no major enterprise-grade software company has the necessary AI expertise to reconfigure its product suite, they resort to acquiring AI start-ups to bolster their capabilities and ensure a smooth integration of AI into their workflows and operations. This trend creates a compelling market opportunity for specialised enterprise AI businesses that offer solutions designed for seamless embedding within existing enterprise systems and across different business functions.
The impact of AI goes beyond providing specialised solutions to established industries. It also leads to the emergence of “Embedded AI”, which refers to the seamless integration of AI-augmented services into end-customers’ everyday operations. This integration of AI into various aspects of daily business operations opens up significant possibilities for further growth. As AI continues to advance and transform industries, businesses that can effectively harness the potential of embedded AI stand to benefit from enhanced customer experiences, improved efficiency, and a competitive edge in the market.
AI across enterprise business functions
Sales and marketing
AI has revolutionised sales and marketing, automating tasks such as lead generation and scoring, and enabling personalised customer interactions. It processes vast real-time data, identifying peak intent phases for target accounts and alerting sales reps about crucial events. By strategically timing outreach efforts, sales professionals can achieve more successful conversions. Furthermore, using AI to analyse customer data, identifying behaviour patterns and interests can allow for hyper-personalised marketing campaigns that resonate deeply with individual customers, fostering stronger relationships, increased loyalty, and driving higher revenue and growth for the enterprise. Examples of companies operating in this space include:
UK-based Phrasee has been a leader in this space since 2015. The company has developed an end-to-end platform for enterprise marketing teams that uses generative AI to generate, test, and optimise content for sales campaigns. The company is a frontrunner in leveraging embedded AI to boost the effectiveness of sales and marketing communications.
Hailing from the United States, Regie.ai is a generative AI platform that helps enterprise sales teams research, create, test, and analyse personalised prospecting emails for sales campaigns using a brand’s specific voice and messaging.
Copy.ai is another notable player out of the US. The company offers a range of AI-powered copywriting tools for sales and marketing tools designed to enhance and personalise business communications. Their AI-writing platform automates the time-consuming task of content creation and enables personalised sales emails and messages that empower businesses to connect with their target audience more effectively.
R&D and product development
Generative AI is transforming R&D and product development, empowering researchers, and developers to boost productivity and innovation, securing a competitive edge for enterprises. According to a report by McKinsey, it can reduce developer task completion time by up to 50%, especially for less complex, and repetitive functions such as code documentation and generation. This is highly promising because it signifies not just improved efficiency, but also the freeing up time that can be better allocated towards higher value tasks.
To elaborate, AI-driven analytics have replaced traditional surveys and focus groups, delivering unparalleled insights into consumer behaviour swiftly and accurately. By analysing customer feedback and market trends, AI identifies emerging needs, leading to innovative product opportunities. In addition, it facilitates rapid prototyping and simulation, saving costs and time by eliminating manual iterations and physical prototypes. Integrating AI automates repetitive tasks, freeing employees to explore new ideas, fostering a culture of innovation, and ensuring the consistent delivery of cutting-edge products to meet evolving customer demands.
Pendo, a company headquartered in North Carolina, has developed a cutting-edge AI-driven product experience platform that helps companies understand how their users interact with their software. Among its diverse features, the platform offers product analytics, enabling companies to identify areas of their software that might be causing confusion or frustration among users. Pendo boasts an impressive roster of customers, counting enterprises such as Verizon, Morgan Stanley, Salesforce, and Zendesk among its clientele.
Fusemachines is a leading AI strategy and solutions provider with headquarters in New York and a global footprint across Canada, the US, Latin America, and Asia. The company leverages its proprietary AI engines and industry and tech hubs to enable enterprises from diverse industries to use AI throughout their operations, including R&D and product development processes. To date, the company has established a top-tier list of clients, which includes renowned names such as H&M, IBM, and Time.
Legal & compliance
Embedding AI in legal and compliance operations will be transformative for enterprises. As AI adoption grows, ensuring its reliable operation becomes critical, especially in sectors like financial services where accuracy is paramount. Discussions around monitoring AI will intensify, leading to increased investment and job creation for overseeing and regulating its use. A report by Goldman Sachs reveals that an impressive 44% of legal tasks could be handled by AI (global legal services market size is approximately $900bn). However, comprehensive fact-checking functionalities are crucial to avoid any missteps, as seen in the Steven Schwartz case.
AI’s impact is significant, transforming contract analysis by quickly extracting vital information, identifying crucial clauses, and flagging risks, enhancing efficiency and accuracy. For regulatory compliance, AI keeps businesses up-to-date with changing laws, reducing legal risks, and protecting their reputation. Furthermore, AI’s predictive capabilities assess historical data, identify potential risks, and develop proactive risk mitigation strategies, helping businesses stay ahead in safeguarding against liabilities.
Lexion is a US-based contract management software platform that uses AI to help enterprises better manage contracts. Lexion’s AI engine can automatically extract essential information from contracts, such as the parties involved, the terms of the agreement, and any potential risks. This information can then generate reports and insights that can help legal, sales, finance, HR, and any other department dealing with contracts.
Another US-based venture, Compliance.ai, offers a cutting-edge regulatory management platform powered by AI designed to help highly regulated organisations in the banking, financial services, and insurance industry stay compliant at reduced costs. The platform provides businesses with a consolidated view of their regulatory obligations, automates the monitoring of regulatory changes, and identifies potential risks.
Robin AI is a UK-based provider of legal software that leverages AI to automate contract and legal processes. The company’s machine learning model is extensively trained on proprietary data sourced from 4.5 million legal documents, enabling users to draft, revise, manage, and negotiate contracts at a significantly accelerated pace—60-80% faster—while realising savings of up to 75% on legal fees.
Administrative and finance
By automating repetitive tasks, analysing vast data, and providing data-driven insights, AI empowers enterprises to enhance efficiency, accuracy, and decision-making in administrative and finance areas. In contract generation, embedded AI can simplify the process by swiftly analysing previous contracts with NLP algorithms, extracting relevant clauses and terms, ensuring consistency, accuracy, and time savings. For invoice management, AI automates data extraction, reducing errors, and speeding up processing times, thereby improving cash flow management.
In procurement, AI automates tasks like purchase requisitions and contract management, optimising inventory levels and supplier selection based on historical data and demand patterns. Additionally, in expense management, AI categorises expenses, verifies receipts, and flags policy violations, streamlining the process and improving accuracy through automated data extraction.
US-based Bardeen has developed an AI workflow automation platform that automates routine tasks. Users download a browser extension and select from a wide range of automation templates related to finance, marketing, project management, and more. Bardeen also offers various integrations that enable users to connect the platform to other business tools, such as Salesforce, Zapier, and Slack, to make automating various business processes quick and easy.
Docyt is another leading company in the space. The company has built an advanced AI-powered accounting software that automates repetitive and time-consuming accounting tasks, such as data collection, receipt categorisation, and reconciliations. By integrating bank accounts and submitting receipts, bills, and revenue statements via scanning or email, users can rapidly extract and reconcile data with bank and credit card transactions, facilitating near real-time updates to their accounting ledger.
A new era begins
The transition to embedded AI is already underway and its potential impact will be monumental. As AI capabilities continue to expand and improve in the coming years, AI co-pilots will become an integral part of enterprises across diverse business functions, transforming how businesses operate and make decisions. For skilled workers, AI will be an invaluable assistant in navigating complex decision-making processes, providing valuable insights to tackle intricate and challenging tasks more effectively. Less-skilled workers will witness the automation of repetitive and mundane tasks, liberating their time and energy to focus on activities that bring greater value.
Akin to the advent of outsourcing, the Internet, and the adoption of computers in the workplace, the transformational potential for AI represents a vast and growing opportunity and a ground-breaking leap into a future brimming with unprecedented possibilities for enterprises.
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