{"id":56019,"date":"2025-11-03T15:44:54","date_gmt":"2025-11-03T23:44:54","guid":{"rendered":"https:\/\/svch.io\/?p=56019"},"modified":"2026-06-15T15:28:38","modified_gmt":"2026-06-15T22:28:38","slug":"ai-is-transforming-marketing-insights-from-babson-and-darden","status":"publish","type":"post","link":"https:\/\/svch.io\/es\/ai-is-transforming-marketing-insights-from-babson-and-darden\/","title":{"rendered":"AI Is Transforming Marketing: Insights from Babson and Darden"},"content":{"rendered":"
\n

<\/h2>\n

Generative AI isn\u2019t just changing how we create<\/em> is redefining how marketing works<\/em>.<\/p>\n

A study published in the Journal of the Academy of Marketing Science (2025)<\/strong> by Dhruv Grewal<\/strong>, Cinthia Satornino<\/strong>, Thomas Davenport<\/strong>, and Abhijit Guha<\/strong> explores how Gen AI is reshaping every layer of marketing strategy<\/strong>, from product ideation to customer service.<\/p>\n

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\u201cGenerative AI (Gen AI) will influence how marketers interact and communicate with customers, help create and deliver marketing content, and inform methods for developing new products and services.\u201d \u2014 Grewal et al., 2025<\/p>\n<\/blockquote>\n

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\ud83d\udd0d\u00a0What the Paper Shows<\/strong><\/h3>\n

1\ufe0f\u20e3 Analytical AI vs. Generative AI (Table 1)<\/strong><\/h4>\n
\"\"<\/figure>\n

The authors contrast \u201cAnalytical AI,\u201d which predicts<\/strong> and optimizes (e.g., next-best-offer, optimal price, fraud detection), with \u201cGenerative AI,\u201d which creates<\/strong>\u2014marketing plans, ad copy, social posts, synthetic respondents, even first drafts of complaint replies.<\/p>\n

\n\n\n\n\n\n\n\n\n\n
Function<\/strong><\/th>\nAnalytical AI<\/strong><\/th>\nGenerative AI<\/strong><\/th>\n<\/tr>\n<\/thead>\n
S-T-P<\/td>\nPredict if a customer belongs in a target segment<\/td>\nCreate the first draft of a marketing plan<\/td>\n<\/tr>\n
4 Ps<\/td>\nPredict optimal price \/ next offer<\/td>\nCreate ads, product descriptions, or social posts<\/td>\n<\/tr>\n
Research<\/td>\nPredict survey times, analyze data<\/td>\nGenerate synthetic respondents, summarize interviews<\/td>\n<\/tr>\n
Sales<\/td>\nPredict leads<\/td>\nWrite sales scripts, act as sparring partner<\/td>\n<\/tr>\n
Customer Service<\/td>\nPredict complaint sentiment<\/td>\nDraft replies, summarize recurring issues<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/figure>\n

In short: Analytical AI tells you what to do; Generative AI drafts how to say it.<\/strong><\/p>\n

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2\ufe0f\u20e3 The Generative AI Selection Framework (Figure 2)<\/strong><\/h4>\n
\"\"<\/figure>\n

One of the study\u2019s most practical contributions is a 4-quadrant matrix<\/strong> that helps marketers balance speed, cost, privacy,<\/em> and control<\/em>.<\/p>\n

    \n
  • Q1 (Fastest, least control):<\/strong> e.g., summarizing online reviews with ChatGPT. \ud83d\udd3a Highest privacy risk | \ud83d\udd3a Highest speed | \ud83d\udd3b Lowest accuracy | \ud83d\udd3b Lowest cost.<\/li>\n
  • Q2 (Slower, more control):<\/strong> generating social-media content with human editing. \u2696\ufe0f Better balance of accuracy and privacy but slower.<\/li>\n
  • Q3 (Faster custom):<\/strong> e.g., in-store product locator using internal data. \ud83d\udd3d Lower risk | \ud83d\udd3c Higher cost | \ud83d\udd3c Higher accuracy.<\/li>\n
  • Q4 (Most controlled):<\/strong> using a private model like BloombergGPT for SEC filings. \ud83d\udfe2 Lowest risk | \ud83d\udfe2 Highest accuracy | \ud83d\udd34 Highest cost.<\/li>\n<\/ul>\n

    This model helps executives pick between general LLMs<\/strong> (ChatGPT, Claude) and custom or multimodal systems<\/strong>\u2014depending on how much privacy, precision, and human oversight they require.<\/p>\n

    \n

    3\ufe0f\u20e3 Research Avenues (Table 4)<\/strong><\/h4>\n
    \"\"<\/figure>\n

    The authors close with a call to action for marketers and policymakers. Their framework proposes three future priorities:<\/p>\n

      \n
    1. Gen AI Inputs:<\/strong> How do firms choose between general vs. custom models? What ROI trade-offs come from higher privacy and IPR protection?<\/li>\n
    2. Gen AI Outputs & Human Augmentation:<\/strong> Which tasks should remain human-supervised? How can biases and ethical risks (deepfakes, misinformation) be mitigated?<\/li>\n
    3. Regulatory & Societal Impacts:<\/strong> Can Gen AI enhance or harm human creativity and social skills? What regulations best encourage innovation and<\/em> accountability?<\/li>\n<\/ol>\n
      \n

      \u201cTo mitigate biases, it may be optimal to manage not only the algorithm, but also the inputs and human augmentation process.\u201d \u2014 Grewal et al., 2025<\/p>\n<\/blockquote>\n

      \n

      The paper details how global brands already test these ideas:<\/h3>\n
        \n
      • Vanguard<\/strong> boosted campaign conversions +15 % via AI-generated LinkedIn ads.<\/li>\n
      • Unilever<\/strong> cut response time 90 % using Gen AI-assisted replies.<\/li>\n
      • Walmart<\/strong> saved 3 % in vendor-negotiation costs through chat-based automation.<\/li>\n
      • Emirates NBD<\/strong> increased credit-card leads 177 % with AI-personalized offers.<\/li>\n<\/ul>\n
        \n

        For executives and marketers, this research offers an academic foundation for what we teach at Silicon Valley Certification Hub (SVCH)<\/strong>:<\/h3>\n
          \n
        • Strategic Readiness:<\/strong> Choosing the right AI-human balance.<\/li>\n
        • Governance & Trust:<\/strong> Managing privacy, IPR, and ethical risk.<\/li>\n
        • Capability Building:<\/strong> Upskilling teams to move from using AI tools to orchestrating<\/em> AI systems.<\/li>\n<\/ul>\n

          Gen AI\u2019s future isn\u2019t about replacing creativity\u2014it\u2019s about scaling it responsibly.<\/p>\n

          \n

          \u2728 Key Takeaway<\/strong><\/h3>\n

          Generative AI is the new creative partner in marketing.<\/p>\n

          The leaders who master its frameworks\u2014balancing innovation<\/strong>, risk<\/strong>, and human oversight<\/strong>\u2014will define the next decade of brand growth.<\/p>\n

          #AI #Marketing #Research #GenerativeAI #Leadership #Innovation #DigitalTransformation #SVCH<\/p>\n

          \n

          Frequently Asked Questions<\/h2>\n
          \n

          What does this mean for a Chief AI Officer?<\/h3>\n

          Your role is expanding beyond optimizing existing processes\u2014you now need to govern both analytical and generative AI systems with different risk profiles and use cases. The research shows generative AI requires new oversight frameworks because it creates novel content and strategies, not just predictions, meaning your governance model needs to address quality, brand safety, and intellectual property concerns that analytical AI doesn’t present.<\/p>\n<\/div>\n

          \n

          How should we decide between analytical AI and generative AI for our marketing function?<\/h3>\n

          Use analytical AI when you need precision and risk management\u2014like pricing optimization or lead scoring\u2014and generative AI when you need speed and creativity, such as drafting marketing plans or customer service responses. The Grewal study suggests the most effective marketing organizations will deploy both in tandem, with analytical AI identifying what to do and generative AI executing how to communicate it at scale.<\/p>\n<\/div>\n

          \n

          Where should we start if we’re assessing our AI maturity?<\/h3>\n

          Begin by mapping your current marketing workflows against the paper’s framework\u2014identify which decisions are analytical (prediction-based) versus generative (creation-based), then assess where you have AI capability gaps. Silicon Valley Certification Hub’s AI Assessment for companies helps executives conduct this mapping and establish a baseline readiness score before investing in new generative AI tools or training your teams.<\/p>\n<\/div>\n

          \n

          What should our team do in the next 90 days?<\/h3>\n

          Pilot generative AI in one high-volume, lower-risk marketing function\u2014such as first-draft ad copy creation or customer service response summarization\u2014to build organizational comfort while measuring output quality and brand alignment. Simultaneously, conduct an audit of your analytical AI investments to ensure they’re feeding clean, strategic inputs into these new generative workflows, creating an integrated AI-powered marketing engine rather than disconnected tools.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

          Generative AI isn\u2019t just changing how we create is redefining how marketing works. A study published in the Journal of the Academy of Marketing Science (2025) by Dhruv Grewal, Cinthia […]<\/p>\n","protected":false},"author":155,"featured_media":59250,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"advanced_seo_description":"2025 study from Babson College, UVA Darden, and the University of New Hampshire shows how Generative AI is redefining marketing strategies, content creation, and customer engagement. Learn how leaders can balance automation with human creativity.","jetpack_seo_html_title":"How Generative AI Is Transforming Marketing: Insights from Babson and Darden Researchers\n","jetpack_seo_noindex":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[24],"tags":[],"class_list":["post-56019","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research"],"acf":[],"jetpack_featured_media_url":"https:\/\/svch.io\/wp-content\/uploads\/2026\/06\/silicon-valley-certification-hub-alejandro-cuauhtemoc-mejia-ai-marketing-transformation-babson-darden-adoption-rates-1.png","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/posts\/56019","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/users\/155"}],"replies":[{"embeddable":true,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/comments?post=56019"}],"version-history":[{"count":0,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/posts\/56019\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/media\/59250"}],"wp:attachment":[{"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/media?parent=56019"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/categories?post=56019"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/svch.io\/es\/wp-json\/wp\/v2\/tags?post=56019"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}