# Jobs to Be Done framework in B2B enterprise software markets

## Theoretical Foundations and the B2B Paradigm Shift

The "Jobs to Be Done" (JTBD) framework stands as one of the most transformative theoretical constructs in modern product strategy. Originally popularized by Harvard Business School professor Clayton Christensen and operationalized through Tony Ulwick’s Outcome-Driven Innovation (ODI), the framework fundamentally redefined market segmentation [cite: 1, 2, 3, 4]. As articulated in foundational texts from the Clayton Christensen Institute and the Harvard Business Review, the core premise posits that customers do not purchase products or services based on demographic alignments; rather, they "hire" solutions to make progress in specific circumstances, aiming to complete a underlying "job" [cite: 1, 4, 5]. This paradigm shift was famously illustrated through Christensen's milkshake study, which demonstrated that consumers hired milkshakes not for their flavor profile, but for the functional job of alleviating morning commute boredom and the emotional job of feeling satiated until lunch [cite: 3, 6, 7]. 

However, as the framework transitioned from consumer goods to the complex architecture of business-to-business (B2B) enterprise software, a significant misalignment emerged. Generic marketing literature frequently attempts to force-fit consumer JTBD methodologies onto B2B ecosystems, erroneously treating the enterprise as a single, monolithic actor with a unified organizational job [cite: 8]. Peer-reviewed literature, including research published in the Journal of Management Information Systems and the International Journal for Multidisciplinary Research, challenges this oversimplification. Advanced academic models increasingly view B2B transactions through the lens of Service-Dominant Logic (SDL), wherein value is not delivered by the software vendor but is co-created with the customer in a highly contextual, multi-stakeholder environment [cite: 9, 10, 11, 12]. In this view, a B2B product's success relies on resolving a complex web of interconnected and often competing jobs distributed across an entire organizational matrix.

As the enterprise software landscape evolves through 2026, characterized by the exponential proliferation of Artificial Intelligence (AI) and the maturation of Product-Led Growth (PLG) go-to-market strategies, standard interpretations of JTBD have proven insufficient [cite: 13, 14, 15]. The decision to "hire" or "fire" enterprise software is no longer predicated solely on functional utility. Instead, it is governed by coordination costs, compliance mandates, and profound variations in corporate procurement cultures across geographical boundaries [cite: 8, 16, 17]. To maintain its analytical rigor, the JTBD framework must be aggressively recontextualized to address these post-2023 market realities.

## B2C vs. B2B Complexity: The Disaggregation of the Buyer

The primary divergence between B2C and B2B applications of JTBD lies in the disaggregation of the decision-making unit. In consumer markets, the job executor, the product lifecycle support team, and the economic buyer are typically embodied in a single individual [cite: 2, 5]. The consumer identifies a struggling moment, evaluates alternatives, makes a financial decision, and assumes responsibility for the product's ongoing utility. Conversely, enterprise software providers serve a tripartite customer base where these roles are entirely fractured [cite: 5]. 

When a B2B organization "hires" an enterprise software platform, it is not merely acquiring a digital tool; it is forcefully embedding a new workflow into its operational fabric, thereby introducing high coordination costs, integration risks, and systemic dependencies [cite: 18, 19]. This complexity necessitates a fundamentally different approach to capturing, categorizing, and fulfilling customer needs, as illustrated in the foundational differences outlined below.

| Architectural Dimension | B2C "Jobs to Be Done" Dynamics | B2B Enterprise "Jobs to Be Done" Dynamics |
| :--- | :--- | :--- |
| **Primary Decision Maker** | Singular individual consumer acting autonomously. | Multi-stakeholder buying committee averaging 10 to 15+ members [cite: 20, 21]. |
| **Core Job Focus** | Immediate personal progress, convenience, lifestyle enhancement, or emotional satisfaction [cite: 1, 4]. | Organizational efficiency, regulatory compliance, quantifiable ROI, and enterprise risk mitigation [cite: 7, 17, 22]. |
| **Switching Costs** | Generally low and frictionless; predicated purely on alternative market availability [cite: 7, 23]. | Exceptionally high; compounds across legal reviews, data migration, user retraining, and systems integration [cite: 19]. |
| **Sales and Adoption Motion** | Marketing-led, direct-to-consumer, instantaneous transactional conversions. | Product-Led Sales (PLS), lengthy evaluation cycles, multi-threaded consensus-building [cite: 14, 24]. |
| **Primary Success Metric** | Individual product usage frequency and personal satisfaction scores [cite: 25]. | Multi-threaded account engagement, systemic enterprise adoption, and overarching economic outcomes [cite: 26, 27]. |

## Deconstructing the Buying Committee: A Web of Conflicting Jobs

A persistent failure in enterprise go-to-market strategy is the assumption that an organization shares a singular goal, such as "increasing revenue" or "improving productivity" [cite: 8]. In reality, the average B2B buying committee includes ten to eleven distinct stakeholders, with complex enterprise deals often involving up to twenty individuals [cite: 20, 21]. Each stakeholder approaches the procurement process with an idiosyncratic set of functional, emotional, and social jobs [cite: 7, 22, 28].

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 Functional jobs represent the objective tasks requiring completion; emotional jobs represent how the stakeholder desires to feel during the process; and social jobs dictate how the stakeholder wishes to be perceived by their professional peers and superiors [cite: 7, 22, 28]. Understanding the inherent conflict between these stakeholder jobs is the key to mastering B2B product positioning.

The end-user, acting as the primary job executor, evaluates software based on its immediate impact on their daily cognitive load and workflow friction. Their functional job centers on executing tasks rapidly, minimizing administrative overhead, and bypassing legacy bottlenecks [cite: 22, 29]. Emotionally, the end-user seeks to feel empowered, capable, and free from the frustration of navigating clunky, outdated interfaces [cite: 7, 22]. Socially, they desire to appear highly productive and technologically adept to their direct supervisors, actively avoiding the perception of being an operational laggard [cite: 22]. For the end-user, the ideal software is frictionless, instantly accessible, and heavily automated, which often drives them toward unauthorized, "shadow IT" solutions.

In direct contrast stands the IT and security gatekeeper, representing the product lifecycle support team. This stakeholder does not hire software to accelerate marketing campaigns or close sales deals; they hire software to maintain architectural stability and enforce corporate compliance. Their primary functional job is to ensure seamless integration with existing tech stacks, maintain strict data governance, and pass rigorous security audits without exposing the firm to vulnerabilities [cite: 18, 30]. Emotionally, the IT gatekeeper operates from a posture of extreme risk aversion; their job is to feel secure, in control, and insulated from the catastrophic anxiety associated with a data breach or systemic failure [cite: 7, 22]. Socially, they must be perceived by the C-suite and regulatory bodies as diligent protectors of corporate assets, though they often fear being viewed as bureaucratic impediments to innovation [cite: 22]. The friction here is palpable: the end-user's desire for rapid, unsanctioned software adoption directly threatens the IT gatekeeper's emotional and functional mandate for security.

Presiding over this tension is the economic buyer, typically a C-suite executive, department head, or Chief Financial Officer, who participates in nearly eighty percent of enterprise purchase decisions [cite: 20]. The economic buyer views the software through a macroeconomic lens dictated by margin pressures and competitive market positioning. Their functional job revolves around consolidating vendor sprawl, reducing overarching operational expenditures, and securing a highly defensible, quantifiable return on investment (ROI) within a specific fiscal quarter [cite: 27, 31]. Emotionally, the executive seeks reassurance that the capital allocation is sound, attempting to stave off buyer's remorse and the professional anxiety of backing a failed digital transformation initiative [cite: 7, 28]. Socially, the economic buyer aspires to be recognized by the board of directors and industry peers as a visionary leader who decisively drives operational excellence and fiscal responsibility [cite: 22]. 

The success of a B2B enterprise software provider hinges upon acknowledging these contradictions. A product that flawlessly executes the end-user's functional job will be unceremoniously "fired" if it violates the IT gatekeeper's emotional need for security or the economic buyer's functional need for cost consolidation. Enterprise messaging must therefore act as a multi-threaded diplomatic instrument, equipping internal champions with the precise narratives required to neutralize the anxieties of opposing stakeholders across the buying committee [cite: 7, 20].



## AI Integration: The Outcomes Economy and the Mechanics of "Firing"

The technological advancements spanning 2024 to 2026 have fundamentally restructured the enterprise software infrastructure, driven by the systemic integration of Artificial Intelligence and autonomous agentic workflows [cite: 13, 32]. This integration has profoundly altered the calculus of switching costs, reshaping the psychological and mechanical forces through which software is hired and fired [cite: 19, 33]. 

For the entirety of the SaaS era, B2B value creation was defined by an "output logic," wherein pricing models, governance structures, and customer expectations were based on deliverables, feature capacity, and utilized seats [cite: 26]. The functional job of traditional software was to provide a digitized workspace for human operators. However, as AI transitions from an auxiliary copilot feature to the pervasive foundational layer of business operations, B2B markets are experiencing an aggressive structural shift toward an "outcomes economy" [cite: 26]. Organizations no longer hire software to merely facilitate a task; they hire autonomous AI systems to guarantee a specific business result, such as guaranteed system uptime, deterministic conversion rates, or direct margin improvement [cite: 23, 26]. Extensive academic and industry analyses reveal that AI-driven automation can reduce digital content verification costs by up to ninety-eight percent and accelerate analytical procedures by three hundredfold [cite: 34]. Consequently, B2B vendors who remain tethered to traditional output-centric, seat-based operating models are facing severe margin compression and escalating customer churn, as enterprise buyers increasingly demand direct accountability for final outcomes [cite: 26].

This shift has created a fascinating paradox regarding enterprise switching costs. The proliferation of "vibe coding"—a phenomenon where non-technical users leverage natural language prompts to instruct AI to generate custom internal tools, integrations, and CRUD applications—has created an existential threat to point-solution SaaS vendors [cite: 15, 35]. For small and medium-sized businesses (SMBs), AI has effectively collapsed technical switching costs to near zero. SMBs are increasingly firing rigid, expensive SaaS subscriptions in favor of flexible, AI-generated internal workflows assembled over a single weekend [cite: 19, 35]. This has resulted in SMB churn rates skyrocketing to anywhere between thirty-one and fifty-eight percent annually [cite: 19].

However, data tracking deep enterprise replacement rates reveals a starkly divergent trend: enterprise SaaS churn remains structurally unchanged at a highly stable one to two percent annually [cite: 19]. This divergence underscores a critical limitation in how technologists historically modeled switching costs within the JTBD framework. While AI has undoubtedly collapsed the *build time* for software engineering, it has not compressed the *coordination time* [cite: 19]. In the enterprise context, the cost of firing a software vendor does not scale linearly with internal engineering capabilities; rather, it compounds across complex legal compliance reviews, robust data security audits, protracted procurement approvals, and enterprise-wide change management [cite: 19]. The functional job of an enterprise tool is inextricably intertwined with institutional habit and anxiety—the psychological forces of attachment to familiar processes and the deep-seated fear of unknown implementation risks [cite: 7, 19]. AI coding agents cannot immediately resolve these human coordination bottlenecks. Therefore, enterprise software retains its defensive moat not through vastly superior feature sets, but through the immense bureaucratic gravity and relational friction inherent to cross-functional organizational coordination.

## Product-Led Growth (PLG) as a Catalyst for JTBD

Parallel to the AI revolution is the strategic maturation of Product-Led Growth (PLG) and its necessary evolution into Product-Led Sales (PLS) within the enterprise sector. In legacy sales-led motions, the software vendor relied entirely on lengthy discovery calls, speculative demonstrations, and marketing collateral to convince the economic buyer that the product could eventually fulfill the organization's jobs [cite: 36]. The product itself was heavily gated, and the pivotal "Aha!" moment—the visceral realization of value—was severely delayed until long after the contract was signed, the implementation was complete, and the onboarding was finalized [cite: 14, 36].

By 2026, the B2B buyer’s journey has compressed dramatically. This compression is explained by the "Halving Principle," which dictates that for any job capable of being executed digitally, the time from user intent to outcome halves every few years, with AI accelerating this curve exponentially [cite: 25]. Buyers no longer possess the patience for speculative sales cycles; they demand to experience the software fulfilling their functional job instantaneously. PLG strategies perfectly accommodate this shift by allowing the end-user to hire the product frictionlessly via a free trial or a freemium model, effectively bypassing the initial procurement bottleneck [cite: 15, 36]. In this paradigm, user onboarding is no longer a sequential tutorial built *for* the user; it is a property of the product itself [cite: 25]. Utilizing frameworks like the "Bowling Alley," modern AI-native SaaS products ask for the user's specific JTBD at the moment of sign-up and dynamically alter the entire product interface to deliver that precise functional outcome within seconds, utilizing product bumpers to guide the user toward activation without human intervention [cite: 25].

However, pure self-serve PLG models frequently hit a revenue ceiling in B2B environments because they primarily solve the end-user's functional job while entirely neglecting the complex compliance requirements of the IT gatekeeper and the ROI demands of the economic buyer [cite: 14]. This strategic gap birthed Product-Led Sales (PLS). PLS acts as the critical bridge, utilizing sophisticated product usage telemetry to identify when a cluster of end-users within an account has successfully hired the product for their daily workflows [cite: 14]. Rather than relying on cold outbound tactics, the PLS representative leverages this behavioral data as a highly qualified entry point. The sales motion then intentionally pivots the conversation away from end-user features and toward the macroeconomic jobs of the buying committee [cite: 14, 27]. The PLS practitioner demonstrates to the economic buyer how organic, ground-up adoption translates into enterprise-wide ROI, and proves to the IT gatekeeper that the platform offers secure, compliant oversight of what would otherwise become shadow IT [cite: 14, 27]. In essence, PLG proves the functional job is solved, while PLS navigates the emotional and social jobs required to secure the enterprise contract.

## Structural Limitations of JTBD in Commoditized and Compliance-Driven Markets

Despite its unparalleled utility for uncovering latent customer needs and architecting disruptive innovations, the Jobs to Be Done framework exhibits distinct, systemic limitations when deployed in specific B2B environments. These limitations become glaringly apparent in heavily commoditized sectors and highly regulated, compliance-driven operational technology (OT) markets [cite: 8, 17].

In heavily regulated sectors—such as pharmaceutical life sciences, financial services data management, or industrial supply chain logistics—the primary "job" is rarely defined by the user's intrinsic desire for personal progress or workflow optimization. Instead, the job is dictated by rigid, external regulatory frameworks and strict legal mandates [cite: 6, 17]. For example, in the highly specific salvage auto auction space, a title processing team is not hiring a new platform to feel innovative; they are hiring it strictly to automate lienholder verification in absolute accordance with complex state laws [cite: 17]. Similarly, pharmaceutical companies hire comprehensive SaaS solutions like Veeva not merely for generic communication, but to navigate the labyrinthine compliance requirements of R&D, clinical trial support, and regulatory commercialization [cite: 6]. 

In these environments, traditional JTBD research methodologies—which rely heavily on surfacing deep emotional and aspirational needs—can inadvertently lead product teams astray [cite: 8]. The emotional job of "feeling empowered" is entirely subordinate to the functional, non-negotiable job of "avoiding federal penalties." Furthermore, success in industrial and construction markets often requires shifting from compliance-driven, top-down siloed scheduling to collaborative, commitment-based execution models, such as the Last Planner System [cite: 37]. If a B2B SaaS tool optimizes its interface heavily for individual emotional jobs but fails to architect the complex, mandated data hand-offs between multiple subcontractors, safety auditors, and legal entities, it will fundamentally fail to be adopted [cite: 37]. The framework struggles when the true "customer" mandating the job is a government regulatory body rather than the human user.

Additionally, JTBD struggles to provide actionable strategic differentiation in mature, heavily commoditized software markets [cite: 8]. When the core functional job is universally understood and effectively solved by dozens of legacy enterprise vendors, merely identifying the job yields no competitive advantage. If the organizational job is "store enterprise data securely in the cloud," knowing this fact does not assist a new market entrant in unseating established oligopolies like Amazon Web Services [cite: 6]. In these scenarios, B2B purchasing decisions are far more heavily influenced by complex psychological factors, deeply entrenched organizational habits, ecosystem lock-in, and aggressive pricing strategies rather than a fundamentally novel approach to solving the core functional job [cite: 7, 8, 38].

## Geographical Dimensions: Cultural Impacts on Procurement Strategy

A critical and often overlooked vulnerability in standard global JTBD applications is the ethnocentric assumption that corporate buyers behave uniformly across geographies. In reality, the profound cultural context of a region dictates the hierarchical structure of the buying committee, the speed of technology adoption, and the specific weight placed on functional, emotional, and social jobs [cite: 16, 39, 40]. To accurately model and predict B2B purchasing behavior globally, go-to-market teams must calibrate their JTBD research to align with regional corporate cultures.

In the United States, business culture generally favors highly concentrated decision-making authority and rugged individualism [cite: 16, 30]. American organizations typically empower individual executives or specific department heads to evaluate and execute purchases swiftly within defined budgetary parameters. This results in a leaner buying committee, often requiring only three to four key decision-makers for mid-tier technology investments [cite: 30]. Consequently, the functional job in the US market is heavily oriented toward aggressive speed to ROI, rapid deployment, and immediate competitive disruption [cite: 16, 30, 41]. The social job of the American executive is frequently to be perceived as an agile, decisive leader willing to take calculated risks to drive overarching revenue growth [cite: 42]. Messaging that highlights rapid value realization and individual executive empowerment resonates deeply within this high-velocity paradigm.

In sharp contrast, the Nordic region—encompassing Sweden, Denmark, Norway, and Finland—operates on a deeply egalitarian, consensus-driven model [cite: 39, 40]. This corporate culture is heavily influenced by remarkably low power distance and sociological constructs such as the *Law of Jante*, which actively discourages overt individual self-promotion and hierarchical dominance [cite: 40, 43]. Flat organizational structures dictate that enterprise decision-making requires broad, horizontal agreement across multiple departments and employee levels [cite: 30, 39, 43]. 

The impact on the JTBD framework in Scandinavia is profound. Procurement cycles are notably slower and highly deliberate, as the buying committee works painstakingly to ensure all voices are heard, psychological safety is maintained, and objections are collectively mitigated without coercion [cite: 30, 42, 43]. The social job of a Swedish manager is not to act as a solo corporate visionary, but to serve as a humble facilitator of team harmony, trust, and collective agreement [cite: 40, 43]. Furthermore, emotional and functional jobs in the Nordics heavily weigh environmental sustainability credentials, strict GDPR privacy compliance, work-life balance impacts, and long-term service continuity [cite: 39, 40, 42, 44]. Software vendors attempting aggressive, top-down American sales tactics will fail; instead, they must arm their internal champions with highly transparent, collaborative documentation that addresses the entire collective team's concerns [cite: 16, 30, 44].

Japan presents an entirely different matrix of cultural variables. Japanese corporate culture is characterized by extraordinarily high context communication, deep uncertainty avoidance, and formalized, rigid hierarchy (high power distance) [cite: 45, 46]. Business decisions are rarely made at the negotiation table; instead, they rely heavily on *nemawashi*—the intricate, informal process of laying the foundation, circulating information, and building quiet consensus long before a formal proposal is ever officially presented [cite: 45, 46]. 

For the Japanese enterprise buyer, the emotional job of risk mitigation overrides nearly all other functional considerations [cite: 45, 46]. Japanese buying committees view the purchasing process not as a transactional software acquisition, but as a long-term, highly integrated partnership. They evaluate the vendor's financial stability, corporate reputation, and relational trustworthiness as rigorously as the software’s technical architecture [cite: 30, 45]. The functional job extends far beyond the immediate task of the software to encompass how the technology holistically integrates into the precise, overarching process chain of the entire manufacturing or operational entity [cite: 45]. American messaging emphasizing "disruption," which implies volatility and untested change, will actively trigger severe anxiety forces within a Japanese organization, causing the buyer to definitively reject the product to preserve institutional harmony and avoid the catastrophic social job failure of losing face [cite: 7, 45, 47].

## Conclusion

As B2B enterprise software markets mature through 2026, the application of the Jobs to Be Done framework must evolve from a simplistic tool for feature prioritization into a highly nuanced, multidimensional strategic instrument. The enduring misconception that an enterprise "hires" software to solve a single, unified functional problem remains a dangerous oversimplification that derails countless go-to-market strategies. Successful enterprise software deployment is entirely contingent upon navigating a labyrinthine buying committee, where end-users, IT security gatekeepers, and economic buyers harbor deeply conflicting functional, emotional, and social jobs.

While the advent of Artificial Intelligence and Product-Led Growth have fundamentally accelerated how users discover and extract value from software—effectively shifting the market from a legacy output-based model to a highly demanding outcomes-based economy—these technologies have not erased the profound coordination costs and integration barriers inherent to enterprise adoption. Product leaders must also exercise intellectual honesty regarding the boundaries of the JTBD framework. In compliance-driven markets, rigid regulatory frameworks routinely supersede individual desires for progress, and in commoditized spaces, psychological habits often outweigh functional innovations. Furthermore, global expansion requires acknowledging that cultural paradigms drastically reweight stakeholder priorities; an American buyer seeking rapid execution requires a vastly different psychological engagement strategy than a consensus-driven Swedish committee or a highly risk-averse, relationship-focused Japanese organization. Ultimately, market dominance in the contemporary B2B landscape is achieved by deeply understanding the intricate web of human motivations, organizational anxieties, and cultural constraints that define the modern enterprise, and engineering a holistic strategy that resolves these conflicting jobs seamlessly.

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16. [growthimpact.ai](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFzMCW2Fjt61YEy2AtqrXatrPRei4xxsID5pZKmuB-0Zuo6ZIzZPyY96mWbe8orzUW57Y8Z7blhR-FHQrC_YoVMqck_Nc6sf_pE_L03myd2llmTDBflDdbidhitbh-BqQgZo6hQ7sdocjSzZPk7ZXl9X-u28KRpGqo_nQ0G7_x2ANqZyXfW-JDfFc7OcUTrw5k4IAc=)
17. [ijfmr.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGR9fqgnPMwoIza7o9rIlkmG6Y5MhjNQ1GerHvNcQpY60Ax7EItv2Vxh5afT9eFwhwUN7Rvyhxy7de7R1GXcOk6MBU4TOEzRskM4D4JgLFNvxeHyxUF_szKJTSqqivIawNtYpE=)
18. [insightpartners.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEothXS1wkSEixpZCgaAKXkdjWPU1G6ebYSzkuKa7IMz-M0t1xJd8TL0yE1I6mwHsErlanKd6OpZifIDLUShhFA2HdtUlj9TqnsRYMg1Q4QfVTDnTSOphdCNS32Q6zXz-I4NpzgF_rdNXiqxCP5IOFlSuiyL2RlkaXgc-FtWH2gAQa6C-vqAzAF_xIAjqYIdRum2p0iaMVKm8xcAIHWepCc5pioq1y1Uyj3JzTyg0BgkxlwKOV09Btr)
19. [medium.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEBafA6vXxlSFAl4G8WhG-AM-3U92OqvuugkWLEvq4ACGwaKurkoeNCVFXulNGacvQ5uKnk-QC-_YeiBuXiqb8CTdP3g3wHUrE8MzI4DRzZnljdlXDzEFEuijHwVaj5rILe43YRBwU1urF1fViOOb9oy_akKtvzkfXZjOgUtQuNO90mjF09S8pYCkV1STc8Irsec73N4VfXv54=)
20. [prospeo.io](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEgrnjQ4lWjk_UENNSpZvtdrcy4q9JBI_Oxki6RTF4Nk1pvP1OM1NsVxuMUZdjZEHcRksb9ixQREuLiu_cCg5bSpYat_N8f6pr-BIUHu0GECeKeb_c4XFkj)
21. [dock.us](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE5KmZsQ8b8DJCDqyAllmSA89qarCXpCgkqnVO8vVppTWOHQ26TAB0HbC4oHaUXoqDBba8_jwEKw4S5nWE7IJpTHSoivv7WncoaS_FmVr_3rlZjQWulVJpA9p_2xTQlVdANbF8=)
22. [umbrex.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGrwOH5p19jZNvSXiTNqFK3bgQLYWEJWG8xjrI-mBaDpNnJkqBWIB4Jv-K2aFcqBjVsjzKYNQLSa0tM6nwhFogKU4ATmip7jSPHu3Lm-MQq7uzXotBSbJSlJxdxqJI--87FEuGIKJ5sKxd2XRDjHipkK9yTbLlrgfNivZV7wsSbxluP5Z7P7oLlMHg3Z0_n-Jo=)
23. [futuresearch.ai](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFomc1QMGdnb69WqQlRFgCJas0xJvxlX2VGJThPHICCf1c_wypr-KL14oNX5JulBTTBQW4blHd6Qfn7u12mMC3M3xiQHgCvqm9euSwwoePljaIOXFOGBFyFdk7aiMi3Aslu_hICRTc=)
24. [twenty-one-twelve.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHh_aRvc_9MiEW7bVSP4_2UNy9_eaAOtIvNBQB-YWXehn5wRiwYe85em_UaWEOExeFuEvth_b_DJ_y0cli25lUT8iblaQONzIxW3ljDkICljnSYhiPepgqANvcPX35DY0CHOZuFqSABUKyM8B5_k_GtxkJHWEqqlL38MCwkH3e1TZf2a_gV4g==)
25. [userpilot.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGL8TAN3LXIOV0NymyaoWRZZumnUokAfy_c_cKdRUrRuGvh_F0DmMG8HOUvP0QfdQK0vNPrHRVB0Fhhz5pi0a85e2NO4xVBZytAZlD98DApwVOO_4l3upoGHYr4BdGju7Kf)
26. [medium.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFGCZm-RZzc85BFsnBeVePDcpYjIfddL2VcXGaeNm1D6Pjw296cc3QZ7hjFQJfZAiM4pz1t6ta4D_uOd1pGiwx0uA_N78YL27wmz819pxQG4MVRcRwVK5t02eDm2h13lUeZroAB3xQGgxHPgK9eL6zDzle0-SNCJbe2j0_XMlqIkkY5TwzU2A8POTRDoZKhXf-DjMDqghnMNNLKrbVAtOGakukVGTbpD2Jrdwwfu1y5FaaZjBw=)
27. [openviewpartners.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGIfL3hM6mD7KohP4Gg3Do-ATujDHav7kfIwqkq7yOHlrHwBxVTLMQxNwwnqyetr0xj9LJbHVX8T_QprjfFwxyyJNyZ8C8VhPFW2jjcalG5clJAzBN6vRK2Me9HrZf6h8MY9n1nQtMbBXX5TmZ1yf8ePneylWYxNrS59kWV7pH6btjMCg==)
28. [velocityengine.co](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEvQsfImYk3ZVntDaCVhr8iuDX-xXG3SF6fBEQAv8olxQo05xUi_bXjawk_4AbCauVWCOIquvnehsYwEpJ0ZZwI3MPTWOwZXTf9dMQqCzdg77TTihyfY0C8-AesLpOwDWYgWx8I4oCNkiECV9XjXwwx06ROOpE7s8yO6PiQX70EfwhgMr9aTnFtjsC6giTrpBgf2x8Sf2bMbB5I8ovj9-gw7isMkxtOL4TvGAgmW_qWvphKwcRjejruoR8=)
29. [pymnts.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHN7qg7h4FD3ey-q-O6TgcC2JzdGY_PMbB_OIGmEHuVfS3PUi98YOetWmVFeut--j9zktOQQJ3dlUQjLmaqLZgPCDWhe4ItkaGKfleiIj1NRonDb096DiAZZMHpPLEeUYyE6yonfYc-KWN249OjI2DKM-ouZN4eHovNQdv4vJ3yudRksd5sysfNAzaqD-UP0oI1rdjPBGa64afwOXrbKFJDW-TsDw65WIkN6gJCUoR4qw==)
30. [aexus.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGFzbVqo3Z_X51R5-b8RvK4ITA6vyUQwyg4wtEwn_0ZqktalGJl5hQsEtXlTG3rj5sZ2uokCAQYnUeQxbybCX6AxVQ1nlrllaGNAXxAQ6MrIxm6X8qp0tbTTO0zIRu6n1BY0Id4C18wZwzG0mT-dv10Kba1ymZ7mJk6HwwyFbtx9snL2bxnOpsv)
31. [forbes.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEMqRqk2CZaHV2i8b5cQH6LkiLD0xOMXdGTpA7Xwnk53cfV60MPb4j6yjf1GitkXRH6cWEv23JyLdlLOk7BpxHiUqoyMmijYobcUwbVEhJJNi6qDyH9pVtMnTNyKoShQZja11fN6U-ipG-cK7qq6iGrQArs6u-zEbKHGAsoZ9paRmP7mNcEpVEGjjMIN4ZtlnrII-YRDQXkDivzZXkaXpH9cQJm8WnqEJvLiMIKkw==)
32. [nowthenext.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHJZF-xv8DBmmcMmIKCypw7Q3fzd9v_6wvq2LsLaQUohV2GPQKCJPIu-oGIiBFL0EwX3mGuCkQAY3gq1O5D0O8d5e0Rvw4uLH0lLieyvHzNcuPKxYgfbb4TVaU-zUTpuQ_BvQr1Ajeqwpb6_6HT9DZr3FSJMeXER6Wurb_cNWxTWbFr)
33. [forbes.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFqrEEn6P43RUQvTB5oXRPRx9gytpJu-qC2U7Ad2P_Ka9hk7PH2oUamB90gj6P5-B9Aqa1FrpcG_yRvFAKv7OAi0aZk4UgTCUE1cUOLJhK4P0gAzePmBnV-dfcxtjoA65Yqfd3vzC2TtkHOQ-HJ--1QUFVVIdDUp7DcfP6t7bpYw8YXM2cqfhHIO4z6Olc0lKndyZWVarD6ZrEg1Ze1)
34. [aimjournals.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFyhZmHgP34Md-K9XP5rtZjjcT6a4I4UxGWduOc0Mwn3wVNb7B3pz8807aRMxrVhM4DQYcp4ByGGrD--Xni5iEoo8UvTYA-rkfAAxYnFUN3Ppx_Stk902b7qZhyKRGbikj3hgBzUSgl1DQ1zN-uoM0=)
35. [nmn.gl](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQES4FtEfLTOBREkCeY-HhXSb89xHBo-kNmwlUBpeg16c5UXEGdsXty7oD-5EkIr-Qwvc7AiqX7z-alfEho5C8V7QW8RHsOqZxJdv32rciQFPEA9YnpWfqtGixyXf0Y=)
36. [chameleon.io](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHtxupcInBrk93gBrjeWteSViuWK-FY7ScWRvgPdDG2qdsla8G9tI_svgIYWWTPgupo3fJIziY8VeXbn7NvHiYgNb3awQJpJ2ph4Z1vFyMRMO9JUQgc8--FracCEkYI7h9Nvq60sa9d8ArtgetzRuA=)
37. [midion.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHCLdHKUsvO-yjUIcxRDViNiPzAvAC-sj92XE2eQrDHHG-HpKE6p8nS-iyZdjkqCezZ5O-0LPn1IaedDxRKVZ1lcqvM3iXhT79MN7WXYaTYprM9pYg=)
38. [oecd.org](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFgYWKHWI8KfRFtoi_RGxIkim_IYHYlHdpAlwtycOsbXUey2_A8NssDnMR7GQ950zdEat2bfaqGE59-kU_HWKUF56X1jITTXe0NPGoO63qACJxRvXruGrIWnqtpBBqjjj3Y-sIvhb_sq-enad45TXwy94PT-wyciR7xTpO-J-slr4pcvXuzqUT2y6VyTkFD4grhZdWJF2zCleKpq6jpUNP8ySJcDGrII1nfLgjRF7Nd8gpMwmHYJNVYpNU=)
39. [pertamapartners.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGDR-ghEhXfv9g7aghlKGoVvLPh2xcgzKYRkwTowCdPC6qS8h9JZmFgX0G43T1nF2-NznRb0ivmVQwxMGt1q-20Rjuignw8TZnv1C-xtyjl3qNevzZpSRWhELLE4KyIgqM4RIB0GJMwPG8VlDm6N5Jq9RC_)
40. [scandicorp.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFmVoX8tEaV2EEa3Vs5WYu47o0wEitYyR3uVXjGtRUdSPXra1HdkbRrHW6acRPZLOFSSCZkcdMaNk6d3eaZc1RijPtzJ568HUIWdXyQ0f2NGbjX-zOfhSZtvlZRGVrVH2aGcxU9y6wPq2neP8rJjZT4wPLvF-2Su90222h_)
41. [researchgate.net](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFZCS56M_8X9wlzCQll-il64uewQ69b2Kfrrie27qD2WvqJukq9aZBiuV7zoRBLoK5oZD0KgsQzkSbSNyLp-6AkxsJsba72mv0lCJGMRocA194etetlRSfQrSjje3JqhggMU2K1TyqYCz1aPL1ThsU2HXNpKndauZ93xPrUZjhOyEfTziIdc3hQIxEfFWel4VnbItQTVk9zpX9K-Sd38nQidA98HK_C7V9KShTrJyXx9JypxeAr7PBO)
42. [nlsdays.com](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHAcqDMzVPZ7T8hjL3dEnS5R3ojxCqioMtlM6GT11zR8AnsAZQj8ALckce0S3ZK8WoKmU4buObcGnYVx-Rj-dvTnTm2mzlhnFXJTheJ5--l4tiN5-AMVCnaDTwCheRZLmwYAb6rzhIYPziQpBXcnziTrSiM4Mn5SbDkzwUWCOpblNA94pTr_HA=)
43. [jobshark.eu](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEbhnZrKo_LhJPdd8TxqDk5VMK_FZ3sWRif6dupnz1Ocvve6IG0ZwKb27U1899fB30X31h3jwKZ1z_7JXLYZSBqNj8MbX-8Ql7S3wIWHbm-WIH2g2eRB0ihFHWYG1QBRWw6dLwv5uNihpQdcbrYg8N9da3oGkU6YmzpZ2bWrS1jeja_4GwvdTUEb-witFRb7VX1H-keQMmhQ3yH-wcf97u7Amga6DAkQacWZz92hsS2ad2LRkjK5xtvpGVI2xGoKq08)
44. [salescaptain.io](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGLKf4MtqqC_wz4975ZrrcPJppStqsCt30I0JUWpuTxDWn0mC67giVBxnYPLrtxwuxXE41iRvTPXcXYr7PZ7bJUJ3hgDUrxki9zLPdRlLZFjpk6HP1XXahaTMx8dAiIIZyowsraA8kaJyNQrra_xlwIB_T2GvsA1AZmQDOwceB6aGf572DEtp3aKyzTcz00LyZh)
45. [shu.ac.uk](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH1PBr1svkLBG5aZMk0j7V5idwYGn-wAN9J4Io45MiS926OztTd9OCU1sDgssINyaaBCNpJF9rXv1XC2DlFQJ5LCijwkGIkmi04Vq0MAUhm5nlfv3ggsKc1HGPHcZcC-hMGw2o90kK7uwxTDAjq4XdtHa-Mcy4JU8eQ9dGccGLH06-kgwzDQ_k=)
46. [ase.md](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFeXFI1gtEFClwBTSgdo0ty7rh1iSdDWiNW9LC1qalCXFj-eZHbCZcXzZPMaW4zYrWf2xd-027fenZML7Qo-DDHomUlsN4bk3OEJgY4LCMU43aYwkHj6FCl8GmIOsbtjEd92G-XW7e6xc93eK9DojJ34TVRcfkBj6ce260kqL4VV_tKVxMph5pPrpHH5EseXhjTzxmisfeg5PPTZdpWtUqudjncV1BvQ05b_cLX50wiTaJEgP6m8l7Qa-MZtpnGTOBQL-AbmezXonEN5r_HftD3tw==)
47. [fu-berlin.de](https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF5fMDH3YCDZcznIMTAe8KDHCtFGDmwilins_TBGfUHBwjFC2fi_2zYfaDoC1zwbOaLBxjXmf13X98JmLpYHCpGTz0act0fA15RRXv6y6pUsOITX0qZgZ5rEXHyjo5yeTD4Lau2W2uk0ln94qn3P3WOusBiIUgnpQZs12HmmQD3d2zZtzhoJ_q9LP55bpbwTwgsJZfCsMqWUej8MRuSGZZdiZNWvEkgDivpMypOKd-m9zwqtcnL)