Morgan Stanley (NYSE: MS) has announced the 2026 global cohort for its Inclusive & Sustainable Ventures (MSISV) accelerator program. The firm selected 24 organizations from thousands of applicants to participate in the five-month initiative.

The cohort comprises 20 startups and four nonprofits operating across the Americas and Europe, the Middle East and Africa (EMEA). Each selected entity will receive $150,000 in equity investment or grant funding, alongside access to mentorship and the firm’s global network.

Program Structure and Focus

The accelerator aims to help early-stage innovators develop and scale their impact. Founders will work with a dedicated MSISV team, Entrepreneurs in Residence, and senior Morgan Stanley mentors. The program concludes with a global showcase and demo day scheduled for February 2027.

MSISV targets solutions in four thematic areas where the firm sees significant potential for measurable impact:

• Environment
• Health & Wellbeing
• Economic Empowerment
• Education & Human Capital

Cohort Breakdown by Sector

The selected participants span diverse geographies and sectors. The distribution across the four focus areas is detailed below:

Jessica Alsford, Chief Sustainability Officer at Morgan Stanley, stated that the program connects early-stage innovators with expertise across the Integrated Firm to support their long-term growth goals.

Historical Context

Since its inception in 2017, MSISV has distributed more than $40 million in capital to over 160 organizations. The 2026 cohort continues this effort to catalyze innovation for a more inclusive and sustainable future.

Morgan Stanley says white-collar workers facing the greatest exposure to artificial intelligence could capture some of its biggest economic benefits. The bank highlighted productivity-driven wage growth and wealth gains as key drivers for this group.

High-income, college-educated and city-dwelling workers are identified as the primary beneficiaries. According to a report published by Business Insider on Sunday, these groups stand to gain from AI through productivity gains, new job creation and longer-term disinflation.

AI’s Impact

Morgan Stanley economist Heather Berger noted that younger workers could face greater disruption as AI takes over routine, entry-level tasks. In contrast, older workers could see productivity gains without being fully replaced.

"In terms of job creation, it is still early, but new AI-related occupations have so far been aimed at these same CHIC consumers," Berger wrote. Morgan Stanley uses "CHIC" to describe college-educated, high-income, city-dwelling households. This group is considered particularly exposed to AI-related changes in the labor market while also standing to benefit from productivity and wealth gains.

The entry-level risk presents a different concern. Former Microsoft President Jeff Raikes has warned that replacing early-career work with AI could limit opportunities for younger workers to develop critical thinking and professional judgment.

Berger also wrote that AI-related job postings have been targeted toward higher-income consumers with experience in highly exposed industries.

Productivity And Wealth

Morgan Stanley has previously said AI could raise productivity without causing widespread job losses, depending on whether the technology primarily augments workers or replaces them. The bank has also pointed to a potential longer-term disinflationary effect as productivity gains from AI spread across the economy.

AI could affect asset markets and household wealth. High-income households hold more equity wealth relative to annual labor income than lower-income households, making asset-market gains an important part of how AI could affect spending.

What the Numbers Show

The divergence between labor market risks and asset wealth concentration suggests that AI’s economic impact will be unevenly distributed. While entry-level roles face automation pressure, the wealth effects of AI will likely accrue disproportionately to those with existing equity exposure, reinforcing income inequality rather than broadening it.