How Genai is Changing Sales Processes

From MIT SMR - how 14 companies across a wide range of industries are generating value from generative AI today: McKinsey built Lilli, a platform that helps consultants quickly find and synthesize information from past projects worldwide. The system integrates with over 40 internal sources and even reads PowerPoint slides, leading to 30% time savings and 75% employee adoption within a year. Amazon deploys AI across multiple divisions. Their pharmacy division uses an internal chatbot to help customer service representatives find answers faster. The finance team employs AI for everything from fraud detection to tax work. In their e-commerce business, they personalize product recommendations based on customer preferences and are developing new GenAI tools for vendors. Morgan Stanley empowers their financial advisers with a knowledge assistant trained on over a million internal documents. The system can summarize client video meetings and draft personalized follow-up emails, allowing advisers to focus more on client needs. Sysco, the food distribution giant, uses GenAI to generate menu recommendations for online customers and create personalized scripts for sales calls based on customer data. CarMax revolutionized their car research pages with GenAI, automatically generating content and summarizing thousands of customer reviews. They've since expanded to use AI in marketing design, customer chatbots, and internal tools. Dentsu transformed their creative agency work with GenAI, using it throughout the creative process from proposals to project planning. They can now generate mock-ups and product photos in real-time during client meetings, significantly improving efficiency. John Hancock deployed chatbot assistants to handle routine customer queries, reducing wait times and freeing human agents for complex issues. Major retailers like Starbucks, Domino's, and CVS are implementing GenAI voice interactions for customer service, moving beyond traditional phone menus. Tapestry, parent company of Coach and Kate Spade, uses real-time language modifications to personalize online shopping, mimicking in-store associate interactions. This led to a 3% increase in e-commerce revenue. Software companies are integrating GenAI directly into their products. Lucidchart allows users to create flowcharts through natural language commands. Canva integrated ChatGPT to simplify creation of visual content. Adobe embedded GenAI across their suite for image editing, PDF interaction, and marketing campaign optimization. For more information on these examples and to gain insight into how companies are transforming with GenAI, read the full article here: https://lnkd.in/eWSzaKw4 images: 4 of the 20 I created with Midjourney for this post. #AI #transformation #innovation

GENAI + B2B = Five Key Lessons for Deploying Gen AI in B2B Sales 1. Start with the Problem, Not the Technology The decision to adopt #GenAI should be driven by specific business challenges, not by the allure of the technology itself. #B2B leaders must identify areas where Gen AI can drive significant, profitable #growth — such as #lead generation, account management, or service optimization. In some cases, simple automation might be more appropriate, especially where processes are still manual or error tolerance is low. The key is understanding the core business need before choosing the best technology to address it. 2. Keep the Seller at the Center Successful #GenAI #tools are designed around the needs of the sales team. Organizations should assess current workflows and look for ways Gen AI can free up sellers’ time or deliver valuable insights. Solutions should be: a) Impactful b) Clear c) Understandable d) Prescriptive e) Reliable If a #solution fails any of these criteria, it likely needs redesign. The more aligned the solution is with seller workflows and needs, the higher the likelihood of #adoption. 3. Buy the Easy Stuff, Build for Competitive Advantage Most companies use a “buy-plus-build” approach to #GenAI. Off-the-shelf tools can be deployed for basic functions (e.g., #meeting summaries), while high-impact, differentiating use cases (e.g., personalized offers) benefit from customized solutions. The key is knowing when to buy vs. when to invest in building for strategic #advantage. 4. Balance Quick Wins with Long-Term Capabilities A clear #AIstrategy and scalable architecture are critical. Leading companies start with minimum viable products (#MVPs), align their AI efforts across the business, and build foundational capabilities like strong data infrastructure and skilled talent. The goal is to deliver near-term impact while ensuring long-term sustainability and #scalability. 5. Invest in Seller Adoption from Day One Technology alone isn’t enough—seller adoption determines impact. Organizations must prioritize change management, continuous #feedback loops, training, and communication. Involving sellers early, recognizing their successes, and encouraging experimentation can accelerate adoption. AI Centers of Excellence can help drive scale and responsible use across the organization. With these five lessons in mind, B2B sales leaders can turn Gen AI from a promising #concept into a transformative force for growth, #productivity, and competitive advantage - with Thiago F Silva - Inteligência Artificial e Gamificação e Herick Ferreira:

💡 New preliminary but promising research provides what appears to be the first causal evidence that GenAI doesn't just boost productivity—it directly increases firm profits. 💡 A large-scale field set of experiments involving millions of users at a major e-commerce platform found that GenAI enhancements to business workflows increased sales by up to 16.3%, with the largest improvements in customer service applications. Across four workflows with positive effects, researchers calculated an annual incremental value of approximately $5 per consumer. 💡 What makes this study particularly valuable is that it shows GenAI can increase actual sales and revenue, not just help employees work faster. The productivity improvements came through enhanced consumer experience—specifically higher conversion rates—demonstrating that GenAI can create value by reducing marketplace frictions. 💡 The benefits weren't evenly distributed: smaller sellers, less experienced consumers, and tail products derived disproportionately larger gains, suggesting GenAI's potential to bridge capability gaps across marketplace segments. 💡 This research addresses a critical question many executives are asking: does investment in GenAI actually translate to measurable business outcomes? The evidence suggests the answer is already yes. Link to the paper: https://lnkd.in/eFXWcJHg #AI #Productivity 

Your buyer isn't drowning anymore. They're surfing. And Forrester just revealed something fascinating... 89% of B2B buyers now use GenAI across their entire buying journey. Just two years ago, your buyer was: - Drowning in endless content - Lost in feature comparisons - Trapped in research loops Today? They're different: - Using AI as their research assistant - Making faster, smarter decisions - Coming to you better prepared than ever But here's the insight that changes everything... The more your buyers use AI to get smarter... The more they crave genuine human insight. Think about that for a moment. While everyone else is panicking about AI replacing human interaction, you're sitting on an unprecedented opportunity: The chance to have better conversations with better-prepared buyers. Here's the secret: Don't fight the AI. Embrace it. 3 ways to win: 1. Create content that complements post-AI research 2. Build frameworks that spark real conversations 3. Focus on insights AI can't generate The future of B2B isn't about more leads... It's about more meaningful conversations. A few ways to transform your content strategy for conversations: - Stop writing generic “thought leadership.” - Start creating conversation catalysts. - Build insight-rich “buyer playbooks” that help them make decisions. - Equip your champions with internal “mobilization kits.” The future of B2B content? - Meet buyers post-AI research with perspectives they won’t find elsewhere. - Enable deeper, human-driven conversations that stand apart. I go into this shift—and how to navigate it—in my latest blog. Revenue leaders: What's one surprising shift you're seeing in your buyer conversations since GenAI? Share something that made you think differently.

Weekly KPI reporting is broken. GenAI is rewriting the playbook. Every Monday, teams scramble to explain what changed: > Why did conversion dip? > Was it the new onboarding flow? > Did someone ship something that broke sign-up? Most KPI reports are reactive. Static dashboards, crowded charts, and guesswork disguised as insight. Gen AI changes all of that. And, this isn’t just about automation- it’s causality. From what changed to WHY it changed - active explanation through causal insight. Examples: 💡 “Weekly Active Users dropped 14% last week. Likely Driver: seasonality - holidays" 💡 "Activation dropped 12% after Thursday’s onboarding update. Likely driver: mobile load time on step 3 increased 400ms." 💡 "Conversion increased for paid traffic, 85% of the decline attributed to experiment test B and Android users" With causal inference under the hood, GenAI handles the heavy lifting: > Detects anomalies > Surfaces causal drivers > Ranks insights by impact Gen AI tells the story in an easy-to-digest way. No more pulling charts into slides. No more guessing what matters. Just a clean, contextual narrative that helps the whole team align and act - faster. For analysts? Less time building reports. More time doing deep research that drives new insights and growth. This is the shift in Offensive and Defensive Analysis that Elena Verna and I collaborated on in her latest Elena's Growth Scoop article. For product and analytics leaders? Significant value. ✅ You stop losing money on things you’ve discovered too late ✅ Discover deep research-fueled levers for strategic growth. ✅ Build a truly data-fluent culture - everyone understands how the company is growing and why. Insights are available through truly self-served analytics. Instead of sifting through dashboards, Gen AI-powered tools, like Loops, deliver real-time summaries of what changed, why it happened, and what to do next all in plain language, directly in Slack, Ms-Teams, email or wherever your team works. Bottom line: Gen AI compresses the time between signal and action. These new tools are showing us the future of Product Analytics. It’s not just a reporting upgrade. It’s a competitive advantage. And once you’ve seen a causal insight summary show up in Slack, there’s no going back. #productanalytics #AIinAnalytics #CausalInference

Hey Salespeople: Here is a collection of current use cases for AI in sales & CS: ** GenAI in Sales ** --> Draft messaging for personalized email outreach --> Generate post-call summaries with action items; draft call follow ups --> Provide real-time, in-call guidance (case studies; objection handling; technical answers; competitive response) --> Auto-populate and clean up CRM --> Generate & update competitive battlecards --> Draft RFP responses --> Draft proposals & contracts --> Accelerate legal review & red-lining (incl. risk identification) --> Research accounts --> Research market trends --> Generate engagement triggers (press releases; job postings; industry news; social listening; etc.) --> Conduct role-play --> Enable continuous, customized learning --> Generate customized sales collateral --> Conduct win-loss analysis --> Automate outbound prospecting -->Automate inbound response --> Run product demos --> Coordinate & schedule meetings --> Handle initial customer inquiries (chatbot; voice-bot / avatar) --> Generate questions for deal reviews --> Draft account plans ** Predictive AI in Sales ** --> Score leads & contacts --> Score /segment accounts (new logo) --> Automate cross-sell & upsell recommendations --> Optimize pricing & discounting --> Surface deal gaps / identify at-risk prospects --> Optimize sales engagement cadences (touch type; frequency) --> Optimize territory building (account assignment) --> Streamline forecasting (incl. opportunity probabilities; stage; close date) --> Analyze AE performance --> Optimize sales process --> Optimize resource allocation (incl. capacity planning) --> Automate lead assignment --> A/B test sales messaging --> Priortize sales activities ** GenAI in CS ** --> Analyze customer sentiment --> Provide customer support (chatbot; voice-bot / avatar; email-bot) --> Draft proactive success messaging --> Update & expand knowledge base (incl. tutorials, guides, FAQs, etc.) --> Provide multilingual support --> Analyze customer feedback to inform product development, support, and success strategies --> Summarize customer meetings; draft follow-ups --> Develop customer training content and orchestrate customized training --> Provide real-time, in-call guidance to CSMs and support agents --> Create, distribute, and analyze customer surveys --> Update CRM with customer insights --> Generate personalized onboarding --> Automate customer success touch-points --> Generate customer QBR presentations --> Summarize lengthy or complex support tickets --> Create customer success plans --> Generate interactive troubleshooting guides --> Automate renewal reminders --> Analyze and action CSAT & NPS ** Predictive AI in CS ** --> Predict churn; score customer health; detect usage anomalies, decision maker turnover, etc. --> Analyze CSM and support agent performance --> Optimize CS and support resource allocation --> Prioritize support tickets --> Automate & optimize support ticket routing --> Monitor SLA compliance

GenAI is the biggest shift in payments since the cloud. And it’s no longer experimental but being fast hardwired into the industry's core infrastructure. Here's how. 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: 𝗳𝗿𝗼𝗺 𝗱𝗮𝘆𝘀 𝘁𝗼 𝗵𝗼𝘂𝗿𝘀 Developer co-pilots, auto-migrations, and smart test environments mean code is now reviewed, written, and deployed in hours, not days. Entire release cycles are compressing - and costs with them. 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿 𝘀𝗲𝗿𝘃𝗶𝗰𝗲 𝗿𝗲-𝗶𝗻𝘃𝗲𝗻𝘁𝗲𝗱 Call centers are no longer just cost centers. With GenAI-powered routing, instant context generation, and smooth transitions between AI and human agents, payment providers are cutting handling time and upselling during support calls. 𝗠𝗮𝗿𝗸𝗲𝘁𝗶𝗻𝗴: 𝗳𝗮𝘀𝘁𝗲𝗿 𝗮𝗻𝗱 𝘀𝗺𝗮𝗿𝘁𝗲𝗿   From writing briefs to producing campaign assets and testing variations, GenAI enables teams to move quicker and spend less. It reduces reliance on agencies while improving control and consistency. 𝗦𝗮𝗹𝗲𝘀: 𝘀𝗺𝗮𝗿𝘁𝗲𝗿 𝗽𝗿𝗼𝘀𝗽𝗲𝗰𝘁𝗶𝗻𝗴 𝗮𝗻𝗱 𝗵𝗶𝗴𝗵𝗲𝗿 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗶𝗼𝗻𝘀  Reps now get real-time recommendations, while AI takes care of prospecting and closes simple deals on its own. More time selling, less time in the CRM. According to estimates, that’s driving a 30-40% boost in upsell and lower churn. 𝗦𝗺𝗮𝗿𝘁𝗲𝗿 𝗱𝗮𝘁𝗮   GenAI helps organize messy data, trace where it comes from, and surface insights automatically. Turning data from a bottleneck into a growth driver. 𝗡𝗲𝘅𝘁-𝗚𝗲𝗻 𝗿𝗶𝘀𝗸 𝗮𝗻𝗱 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 KYC, fraud, underwriting: the most complex, manual-heavy, error-prone processes in payments are being restructured. GenAI helps extract unstructured data, simulate scenarios, and even write memos and case files - in seconds. 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀   Outbound timing, messaging, and offers are now GenAI-optimized per persona - identifying the best moment and method to reach each customer. Human agents get real-time prompts, AI handles the rest. The result: lower write-offs and improved recovery outcomes. GenAI is breaking the trade-offs that defined payments for decades - cost vs. speed, scale vs. personalization, security vs. experience. The companies leading the next wave aren’t just using AI - they’re rebuilding their payments infrastructure from the ground up, rethinking how everything operates, end to end. If you're in payments and still thinking about GenAI as a trend, then you’re already playing catch-up. Opinions: my own, Graphic source: BCG 𝐒𝐮𝐛𝐬𝐜𝐫𝐢𝐛𝐞 𝐭𝐨 𝐦𝐲 𝐧𝐞𝐰𝐬𝐥𝐞𝐭𝐭𝐞𝐫: https://lnkd.in/dkqhnxdg

We hear from customers who are interested in using the power of AI to help their sales team scale their business. Internally, AI is one of the tools that Amazonians use daily to improve our productivity and do things faster and more efficiently. In that vein, our latest ML blog gives a great inside look at how AWS sales teams are using Account Summaries—one of our first production GenAI use cases built on Amazon Bedrock. Account Summaries help us stay customer obsessed by generating 360-degree views of an account, available on demand and delivered proactively ahead of meetings via Slack. They integrate both structured and unstructured data, including key metrics, real-time web data, ML insights and AI-driven recommendations. Since its internal rollout last year, more than 100,000 summaries have been generated by our sellers, saving them 35 minutes per briefing. Check out our ML blog to learn how Account Summaries are helping our field teams scale and deliver better customer outcomes. https://lnkd.in/gTee4agv Here’s part of a sample output from Account Summaries:

𝑯𝒐𝒘 𝑪𝑴𝑶𝒔 𝑨𝒓𝒆 𝑺𝒖𝒄𝒄𝒆𝒆𝒅𝒊𝒏𝒈 𝒘𝒊𝒕𝒉 𝑮𝒆𝒏𝒆𝒓𝒂𝒕𝒊𝒗𝒆 𝑨𝑰 Generative AI (GenAI) is everywhere. The news. Social media. Even office water coolers. Talk about GenAI disrupting marketing is ongoing. Go beyond headlines like this one, courtesy of Salesforce: “Marketers estimated GenAI could save them up to 5 hours per week” and you’ll often see that these claims boil down to nothing more than easy-win productivity gains, resulting from automation of mundane marketing tasks. So, I’ve been thinking – is GenAI a valuable asset in a CMO’s toolkit? The answer is “yes”, 𝒃𝒖𝒕 𝒏𝒐𝒕 𝒊𝒏 𝒊𝒔𝒐𝒍𝒂𝒕𝒊𝒐𝒏. To achieve long-term success, GenAI use cases need to be deeper than surface-level automation. Winning CMOs will be combining GenAI with existing or new Customer Relationship Management (CRM) approaches, leveraging their human capital, and remaining conscious of GenAI’s limitations. → Combine 𝘸𝘪𝘵𝘩 CRM Consumers demand a highly-personalised journey, which hinges on data, but data-driven decisions are easier said than done, especially with the looming cookie cut-off. High-quality first-party data will be imperative and GenAI will be crucial for crunching out meaningful and usable insights to inform product development, market segmentation and campaigns. → Use GenAI 𝘢𝘭���𝘯𝘨𝘴𝘪𝘥𝘦 your people You may be tempted to cut headcount after making some low-hanging productivity gains, but to do so would be incredibly shortsighted. GenAI is a helpful starting point to generate ideas and create early drafts, and tools like Midjourney support generalists in completing specialist tasks such as graphic design. But for compelling, relatable content, human insight is needed to finetune outputs.   → Leverage GenAI 𝘳𝘦𝘴𝘱𝘰𝘯𝘴𝘪𝘣𝘭𝘺 Risk accompanies opportunity. Questions remain about the data security, potentially reputationally damaging biases, and even the legality of outputs from GenAI, but choosing to wait or ignore GenAI altogether is not an option – employees will find a way to use it with or without your consent. Put yourself in the driving seat by introducing guidance and training early on. GenAI has the potential to support CMOs achieve their sales, growth or lead targets. Who wouldn’t want the 10-20% sales ROI uplifts suggested by McKinsey & Company’s research? But you need to be smart: > Automate the right processes – likely at the back-end where GenAI is invisible to the customer > Have a strategy – don’t use GenAI just because everyone else is, find the use cases that achieve the greatest ROI > Don’t reinvent the wheel – blend GenAI with your existing processes, people, and tools to maximise the utility of your data Have you explored GenAI yet? Thoughts? 👇 #generativeAI #artificialintelligence #marketing Source: CB Insights

It was a pleasure to talk to Paul Morrison at WNS about the impact of AI on retail. We discussed a wide range of topics, from the impact of GenAI on retailers operations, to how it could impact the customer journey. It's such a fascinating area which is changing at pace. Here are a few areas that I think will see the largest impact. ➡ Personalisation at Every Stage GenAI crafts individual experiences, from targeted product recommendations based on past purchases to custom promotions that hit right when a customer is most receptive. It builds customer loyalty by making each interaction feel tailor-made. ➡ Intelligent CX Support (WISMO) Solving the most common customer concern, “Where’s my order?” GenAI-powered chatbots handle this and other frequent queries instantly, freeing up staff and providing seamless, reliable support—no human intervention needed. ➡ Predictive Inventory Management By analysing sales patterns and seasonal demand (and thousands of other inputs such as weather, supply chain disruptions, social media buzz), GenAI forecasts precisely what stock to have on hand, minimising costly overstocking or disappointing stockouts. This ensures products are ready when customers want them. ➡ Dynamic Pricing, Rewards, and Promotions for Real-Time Relevance GenAI empowers retailers to adjust prices, rewards, and promotions in real-time based on demand, competitor trends, and customer profiles. This approach ensures every deal feels personalised, offering customers relevant discounts or loyalty rewards right when they’re most likely to engage. It’s a seamless way to stay competitive, maximise margins, and increase customer satisfaction—all while driving repeat business through tailored offers that adapt to each shopper's unique journey. ➡ Enhanced Loyalty Through Personalised Rewards GenAI helps personalise loyalty programme rewards, delivering offers that resonate based on individual behaviour, increasing retention and turning one-time buyers into repeat customers. Please do have a listen, I really enjoyed the conversation. Apple: https://bit.ly/AP3-L Spotify: https://bit.ly/SO3_L Amazon Music: https://bit.ly/AZ3_L