Gradual

GTM Strategy, Advisor to CEO

“Jill’s unmatched expertise in sales, community building, partnerships, and ecosystems has been pivotal in shaping our product vision and go-to-market strategy. Her unique insights and strategic connections have unlocked new opportunities and accelerated our growth.” – Jerry Li, CEO & Founder

Gradual is a community platform that centralizes all community experiences, driving product adoption and deeper customer relationships.

Strategic Advisor

Stage 2 Capital

Stage 2 Capital invests in early-stage B2B software companies and sits shoulder-to-shoulder with leadership teams to operationalize sustainable revenue growth. We provide expertise and capital to help companies scale. 

Our LP base of 500+ seasoned GTM executives is matched with the strategic and operational needs of our portfolio companies. We involve our network in 100% of our investments, which often includes joining a portfolio company as an executive, board member, or advisor.

In 2018, I helped raise our $15 million Fund I from LPs at Asana, Atlassian, Box, Gong, HubSpot, Okta, Slack, Salesforce, SAP, ServiceNow, Toast, Twilio, Workday, Snowflake, Zoom, and many others.

$15m Fund I, LP, and Associate Member
$80m Fund II, LP
$150m Fund III, LP

GTM Advisor & LP

Klue

GTM Advisor

Competitive Enablement platform that combines market, competitor, and buyer insights.

Raised $81 million from top VCs including Salesforce Ventures, Tiger Global, Craft, and OMERS Ventures.

Advisor

Folloze

Advisor to the CEO

Enterprise customers include Adobe, Autodesk, DocuSign, Okta, VMware, UiPath, Cisco, and ServiceNow. 

Integration partners feature 6Sense, Demandbase, Marketo, Outreach, Qualified, and Salesforce.

nearbound.com

Assisted in the design, launch, and growth of the Nearbound category at Reveal. In June 2024, Reveal merged with Crossbeam, with the unified focus now on driving Ecosystem-Led Growth.

While outbound interrupts and inbound attracts, nearbound surrounds.

Nearbound is essential because buyer behavior has shifted from the ‘How’ economy to the ‘Who’ economy. Buyers now ask, ‘Who can help me solve X?’ and seek out trusted nodes in their network.

Strategy & Champion

Guild

Advisor to the B2B GTM team.

On a mission to unlock opportunity for America’s workforce. When opportunity is as evenly distributed as talent, everyone benefits. Individuals rise, companies grow, and our economy thrives.

In June 2022, Guild raised a $175 million Series F funding round at a $4.4 billion valuation. The round was led by prominent investors including Bessemer Venture Partners, Cowboy Ventures, Emerson Collective, General Catalyst, GSV, ICONIQ, Redpoint, Workday Ventures, Salesforce Ventures, and Oprah Winfrey.

GTM Advisor

LoopVOC

Voice of the Customer software for B2B SaaS Companies. Advisor to CEO & Founder.

Affinio

Member Board of Directors

Sales for Life

Advisor & Partner

Nudge.ai

Acquired by Affinity, a relationship intelligence platform.

Advisory Board Member & Investor

23 years in B2B SaaS Go-To-Market at Salesforce, Eloqua, HubSpot, Marketo. Customer Obsessed. Partner Obsessed. Living-In-Market. LinkedIn Member #320,966

Majored in Customer. Minored in Go-To-Market. Live in-Market. 

24 years in B2B SaaS. Early employee at Salesforce (first 100), Eloqua (#13), HubSpot Advisor (2014-2016), Marketo (2018).

Love startups, especially category creators.

Born Sales. Bred Marketing. Building Partnerships. 

I spent six years in management consulting, 52 quarters in software sales at Salesforce and Eloqua, six years doing professional speaking, 2018 reporting to the CEO of Marketo (acquired by Adobe for $4.75B), Limited Partner "LP" and GTM Advisor at Stage 2 Capital and GTM Fund. 

I started investing in 2012 and maintain my personal portfolio of investments in sales and marketing technology startups. I also started advising startups in 2012 and joined my first Board of Directors in 2016. Four of the companies I've advised have had successful exits -- HubSpot, Accompany, DataRPM, and PartnerHacker. 

My work keeps me focused on the changing B2B buying environment and what revenue teams need to do to evolve their culture, skills, processes, data, and technology. 

****If you want to connect with me on LinkedIn, don't send a generic invite.****

Jill Rowley

Kevin J. Neary

Orcawise

As Co-founder and CEO at Orcawise I lead the following:

- our R&D team building custom LLM's to help enterprises be compliant with EU AI Act. 
- our client consulting team implementing Responsible AI services, tools and training. 
- new initiatives and contributions to the (RAI) Responsible AI ecosystem we foster.  
- speak at events on RAI topics like ethics, sustainability, the future of business & humanity.

Chief Executive

Consultancy on AI ethics, compliance, governance for organizations in health, education, finance and emerging tech.

Fractional Responsible AI Consultant

CeADAR Ireland

Industry Steering Board

IP Commercialization Committee

MassChallenge Switzerland

Mentor Expert Judge. 

Kevin Neary Events

AI Keynote Speaker 

The AI Roadmap

Digital selling ecosystem for entrepreneurs

Event Manager, Host

NovaUCD

Founder and CEO at UCD Campus Company 

Google for Startups EU

Google Scaling Program 

ORCA Media Group

During this time I contributed to the launch, scale and exit for multiple ventures. 

Staffing Firm Founder: Launched and led a staffing firm for seven years, focusing on innovative recruitment strategies and achieving 100%+ year-on-year growth for five years through to the end of the dot com era.

R&D Consulting - Orca Media: Spearheaded an R&D consulting business aiding entrepreneurs in commercializing academic research. Established key partnerships and facilitated 25 successful projects.

Orca BI: Co-founded and launched Orca BI, introducing Microsoft PowerPivot business intelligence solutions to SMBs in Europe, resulting in 1.2% market penetration in DAX niche within the first year.

Connectors Marketplace: Developed an online marketplace connecting micro-recruiters with hiring managers at US multinationals in Europe, enhancing recruitment efficiency by 30%.

Entrepreneurial Support: Advised and supported US-based disruptive ventures in "audience-participation filmmaking" and AI-driven "venture valuation modelling" and "investment strategies", contributing to 2 successful MVP launches before both ventures ultimately failed to cross-the-chasm due to time-to-market and product-market fit issues. 

Signal-Based Selling Engine: Innovated a signal-based selling engine for identifying buying signals and automating social selling messages, leading to a 36% increase in sales prospects for client that following social selling strategies..

Through these ventures, I've navigated the highs and lows of entrepreneurial endeavors in multiple sectors, resulting in some lucrative lifestyle businesses, pioneering disruptive models resulted in some disappointments as well as seamless exits achieved by integrating IP with more established companies.

Business Owner / Investor

Founder & CEO at Orcawise 🚀 AI Advisor 🌍 Investor 🎤 The AI Roadmap Series

Working with AI since 2003, and today totally focused on Responsible AI (RAI). Kevin Neary is a recognized leader and advisor in Responsible AI -  AI governance, compliance, and ethical AI practices. His expertise is technology compliance with the EU AI Act & US guidelines, with a particular focus on AI Risk management, Bias and Fairness compliance in information systems.

As the CEO of Orcawise, Kevin and team is the trusted partner to enterprises implementing RAI practices.

Beyond his role at Orcawise, Kevin is actively involved in advancing AI through positions as a board advisor at leading institutions, including Georgia College and State University's, AI Lab and CeADAR, Ireland's National Centre for Applied AI. CeADAR is one of Europe's top EDIHs (European Digital Innovation Hubs), dedicated to promoting AI adoption among SMEs and public sector organizations (PSOs). Kevin's contributions at CeADAR help make the benefits of AI accessible and actionable by businesses that want to transform and innovate responsibly and sustainably.

A sought-after speaker with The AI Roadmap event series in New York, Kevin educates business leaders on AI Literacy & Ethics. He serves as a mentor/expert/ judge at the global platform MassChallenge, Switzerland, and as a mentor at the AI Ecosystem Accelerator, NovaUCD, University College Dublin, supporting AI startups and the next generation of AI innovators.

🔔 Contribution to our AI community:

▶️ RAI Tools for Compliance 

Orcawise EU AI Act Chatbot - is a customizable LLM designed to help automate compliance with the EU AI Act 🔴 DM me for a demo. 
 
▶️ RAI Services

With two decades of experience, I lead a seasoned team offering consultancy and development services 🔴 DM me about RAI consultancy.

▶️ RAI Training Programs

Responsible AI Training (RAIT) - is a custom bootcamp for companies automating compliance with EU Ai Act 🔴 DM me to enquire about AI training for your team.

🔔 Commitment to the AI Community:

▶️ Steering Board Member at CeADAR, Europe’s top Digital Innovation Hub, facilitating AI adoption for SMEs and PSOs.

▶️ Advisory Board Member at Georgia College & State University, AI Lab

▶️ Organizer of “The AI Roadmap” Event Series to demystify AI technologies and their applications.

🔔 Keynote & Mentoring

Active mentor and keynote speaker, contributing globally from the US to EMEA.

🔴 Background

Previously, I was a business & system consultant (founder and staff member) with a track record of securing over $100 million in "new business". 

Follow me for updates and insights into Responsible AI!

Chief Executive leading AI Transformations with Advisory & Services for Entrepreneurs and  Marketers

🚨 BREAKING: EU Announces Significant Delays for AI Act Enforcement 🚨
The European Commission has just proposed critical amendments to the AI Act that could reshape compliance timelines for AI systems across Europe. Instead of going live next August, high-risk AI obligations will only begin once Brussels confirms that the necessary harmonised standards and support tools are in place, a process whose timing remains uncertain. 

What does this mean for businesses? 🇺🇸 🇪🇺 🇬🇧 

🇪🇺 The application of high-risk obligations for areas like employment, credit scoring and law enforcement might be postponed until sometime before December 2027.

🇪🇺 For product-based high-risk systems, the timeline extends to August 2028.
These "longstop" dates serve as safety nets if standards and specifications aren’t ready in time.

🇪🇺 While these changes aim to create legal certainty and reduce compliance complexity, they also introduce a period of uncertainty. Companies need to stay alert to upcoming developments and prepare for phased implementation once standards are finalized.

🇪🇺 This move reflects a broader effort to balance innovation, safety, and clarity in EU’s digital rules. But one thing's clear: compliance timelines are now more flexible, but also more unpredictable.

Stay tuned as the EU continues refining its approach to responsible AI regulation.

Source: Digital Strategy Europa

#RAIMS #ResponsibleAi

Kevin Neary

CEO at Orcawise | Pioneering RAIMS™ Responsible AI Management System turning ISO 42001, EU AI Act & NIST guidance into practice with Standards, Credentials & Implementation | Author & AI Keynote Speaker

This paper from World Economic Forum via Peter Slattery, PhD address some key components of Responsible AI in the context of operationalizing real-world AI agents.

CEO at Orcawise | Pioneering RAIMS™ Responsible AI Management System turning ISO 42001, EU AI Act & NIST guidance into practice with Standards, Credentials & Implementation | Author RAIMS Report & AI Keynote Speaker

"The paper makes three key contributions. Firstly, it covers the technical foundations of AI agents, including their architectures, protocols and security considerations. 

Secondly, it offers a functional classification that differentiates agents by their role, autonomy, authority, predictability and operational context. 

Thirdly, it suggests a progressive governance approach that directly connects evaluation and safeguards to an agent’s task scope and deployment environment. 

Together, these elements guide adopters with a conceptual blueprint for moving from experimentation to deployment. 

The report highlights the importance of aligning adoption with evaluation and governance practices to ensure that AI agents are successfully deployed while trust, safety and accountability are maintained"

World Economic Forum Capgemini

AI Agents in Action

The opportunity for small and mid-sized economies competitiveness is to pool their resources to develop frontier models or niche sector specific models. The opportunity is even greater for these economies  to pool resources to lay a responsible AI foundation on which to evolve all AI development, at a national(s) level, that is truly differentiated (with embedded governance) from what the large economies are currently doing with frontier models.

"The United States now controls approximately 75% of global AI compute capacity, China 15%, and the EU 5%. This concentration of compute, alongside concentrations of AI development talent, data, and AI model ownership suggests that mid-sized economies likely face insurmountable barriers to independent frontier AI development. 

At the same time, economic, cultural, and security infrastructures are coming to rely ever more on frontier models. States that are unable to develop their own frontier models or access the computing hardware required to train them will have to choose between dependency and weakness: 

• Dependency: if states adopt U.S. or Chinese AI systems, these frontier AI states can then exploit their privileged position in ways that harm dependent states, for example through data theft, service restrictions, selectively withholding frontier capabilities, embedding values in foundation models, and unfavorable terms of trade. 

• Weakness: if, on the other hand, states limit their adoption of frontier systems to avoid dependency, frontier AI states may achieve breakthrough capabilities—in economic productivity, in scientific discovery, in military operations—that create widening gaps in economic and military capabilities. Yet, mid-sized economies are also AI bridge powers, possessing substantial AI development capabilities and resources that, if combined, would allow them to challenge the status quo. 

By working together and strategically choosing their AI development approaches, AI bridge powers can develop competitive frontier models: 

• First, pooled computing infrastructure can support frontier-scale development. [...]

• Second, a significant portion of top AI talent has ties to AI bridge power countries [...]

• Third, while most of the data used to train frontier models is already public, bridge powers could pool domain-specific data and resources for data cleaning and expert labeling efforts. 

• Fourth, bridge powers should make strategic, frontier development bets[...]

• Fifth, building reliable AI represents an unmet market need where bridge powers have structural advantages[...]

A multinational partnership could enable members to preserve sovereignty, have more weight in shaping global AI governance, and lead through ethical stewardship[...]

Adrien ABECASSIS, Jonathan Barry, Imane (Ima) Bello, Yoshua Bengio, Antonin Bergeaud, Yann Bonnet, Philipp Hacker, Ben Harack, Sophia Hatz, Joachim Henkel, Holger Hoos, Kit Kitamura, Ranjit Lall, Yann Lechelle, Constance de Leusse, Charles Martinet, Nicolas Miailhe, Julia C Morse, Maximilian Negele, Kyung Ryul Park, Miro Pluckebaum, Murielle Popa-Fabre, Benjamin PRUD’HOMME-AMICHOT, Yohann Ralle, Mark Robinson, Charbel-Raphaël Segerie, José-Ignacio Torreblanca, Lucia Velasco, (Vijay) K VijayRaghavan

A Blueprint for Multinational Advanced AI Development

Is AI just a 5-Layered Cake: energy, chips, infrastructure, models and applications? What about Regulation - is it an extra layer or is it embedded at every layer?

Automating Business Processes with Generative AI & Data-Driven Insights | Digital Transformation Consultant

NVIDIA's CEO just revealed the real AI battleground. And it's not what you think.

Jensen Huang stood in front of policymakers and dropped a framework that changes everything about AI competition.

"Let's simplify AI into a five-layer cake: energy, chips, infrastructure, models, and applications."

Then he handicapped each layer comparing the U.S. and China. The results should terrify American policymakers.

Here's the brutal reality:

Layer 1 - Energy: China generates roughly 2x the electricity the U.S. does. Their capacity is climbing while U.S. capacity stays flat.

Layer 2 - Chips: The U.S. is "generations ahead" through NVIDIA and AMD. This is America's strongest layer.

Layer 3 - Infrastructure: This is where the gap becomes dangerous. Huang said:

"If you want to build a data center in the United States, it takes about three years. They [China] can build a hospital in a weekend."

Layers 4 & 5 - Models and Applications: The U.S. leads, but it doesn't matter if the foundation crumbles.

Why this framework matters:

You can win on chips and models but still lose the AI race if you're weak on the foundation.
Right now, China is dominating the bottom layers - energy and infrastructure.

The infrastructure bottleneck:

U.S. data centers take 3 years because of: → Fragmented permitting → Environmental reviews → Grid connection delays
China moves in months: → Centralized approvals → Rapid land allocation → Full build-outs at lightning speed

Time is the critical variable.

The country that can stand up 100 new AI data centers faster gets more compute cycles, more training runs, and faster iteration. Speed compounds. China is compounding faster.

The energy problem:

Huang was blunt: "You can't build AI factories without energy."
China has 2x the electricity generation. That powers semiconductor fabs, AI clusters, and everything requiring massive constant power.
The U.S. chip advantage becomes irrelevant if there isn't enough energy to deploy those chips at scale.

What this reveals:

The AI race is now an infrastructure race.
Winning on models or chips doesn't matter if you lose on energy capacity and build speed.
The bottleneck isn't technical - it's regulatory: → Permitting reform → Grid investment → Transmission expansion → Industrial energy policy.

The uncomfortable truth:

America leads in chips and models. But those advantages sit on a foundation - energy and infrastructure - where China is pulling ahead.
If the U.S. can't reform permitting, expand the grid, and accelerate builds, the chip lead becomes meaningless.

You can't win an AI race if you can't deploy compute at the speed your competitors can.
Huang just told U.S. policymakers exactly what they need to fix. The question is whether they'll move fast enough to matter.

Source : https://lnkd.in/g24VcDQZ

Another important post by Sol Rashidi, MBA, because yes, prompt security control is one of the most important Responsible components, right now. For this purpose I developed and delivered a complete #RAIMS™ Responsible AI Management System providing enterprise employees with, not only access to the protocols, but also access to a credentialing system that ensures every role in the organization is aware and fully aligned when it comes to prompt security, and every other component of Responsible AI.

Giving employees access to generative AI without prompt security is like handing a teenager the car keys and hoping for the best.

Here's what is happening with enterprise AI deployment. 

Everyone's teaching prompt engineering. But almost no one is talking about prompt security.

We spend millions on Copilot licenses. 

Thousands of hours training employees on prompt do's and don'ts.

We create elaborate guidelines about sensitive data.

But here's the reality:

When your workforce is under pressure, multitasking, or simply being human, accidents happen.

- Sensitive data gets entered.  

- Confidential information gets used in a prompt. 

- Proprietary details end up training models they were never meant to touch.  

This is where prompt provenance and prompt security come in.

Prompt security = the set of controls that prevent sensitive data from leaking through AI interactions.

Prompt provenance = tracking who entered what, when, and where in your AI systems.

Think of them as the governance guardrails that should exist before you hand over those AI keys.

Because without them, you are vulnerable to:

- Data leakage incidents 

- Data poisoning

- Unintentional pass-through of sensitive information

After 200+ POCs and 39+ applications in production, I've learned this the hard way:

Reactive measures aren't enough.

Training on prompt writing? Necessary but insufficient.

Business conduct guidelines? Critical but incomplete.

The real protection comes from building prompt security and provenance tracking into your AI governance from day one.

So before you roll out that next batch of AI licenses, ask yourself:

Have you established prompt security protocols, or are you just hoping thousands of employees never make a mistake?

What's your experience with securing AI prompts at enterprise scale?

Consultants - your clients are now paying for outcomes, next clients will only pay for judgement and ultimately judgement tied to outcomes. Judgement with embedded Responsible AI will be the norm. #RAIMS

CEO at Plus AI - Stop making slides the old way! Try the best AI for PowerPoint and Google Slides

The billable hour is dying.

McKinsey just disclosed that 25% of their projects are now outcome-based: fees paid on results, not hours. 

They've cut 5,000 jobs while deploying 12,000 AI agents. Project teams that once needed 14 consultants now run with 2–3 humans plus AI.

The same shift is hitting law. 67% of corporate legal departments expect AI to impact the billable hour.

Bloomberg Law called it "Big Law's AI Nightmare": fewer billed hours, lower profits. 

Ropes & Gray (top 10 largest US law firm) just launched a pilot letting first-year associates spend time on AI training instead of billing.

Entry-level tasks like research, synthesis, first-draft slides, workshop summaries, and model updates don't require humans anymore. What used to take analysts a week now takes ~30 minutes with good AI workflows.

And when the workload shrinks, the price follows.

KPMG is investing $2B with Microsoft to integrate AI into audit. EY calls their new model "service-as-a-software." Firms are being pushed from billing hours to billing outcomes, IP, and productized services.

AI is replacing the parts of consulting that weren't adding value.

Clients will still pay for judgment, experience, and clarity. But they won't pay for manual work.

As cities like NY rethink nightlife and  tourism we'll experience first hand how #RAIMS Responsible AI systems are seamlessly embedded in the growth strategies of city experiences.

Faced with the demands of growth, cities are rethinking how they operate - and when.

In New York City alone, the night-time economy supports 300,000 jobs and
generates over $35 billion per year.

From late-night libraries to nocturnal tourism, sensor-driven lighting and #night czars, here are just some of the ways that #cities are leveraging those extra hours on the clock.

The World Economic Forum has published a briefing paper, Unlocking the Potential of 24-Hour Economies, which explores how governing, investing, and designing for round-the-clock urban life can create safer, more inclusive and more economically resilient cities. You can read it here: https://ow.ly/ePpe50XkNBZ

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Kevin J. Neary

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