Top 7 SaaS Platforms Going AI-Native by 2026

Across the SaaS landscape, a quiet evolution is underway. Companies that once sprinkled AI features into their products are now rebuilding their foundations around it. The ‘AI-native’ shift is no longer just about adding intelligent assistants; it is about rethinking what software can autonomously decide, create and optimise.

By 2026, SaaS will no longer be solely about service delivery. It will be about intelligence delivery. The world’s biggest software platforms are now positioning themselves to lead this new phase, one that blends automation, prediction and personalisation at the core layer.

Here are some of the seven SaaS platforms potentially going all-in on AI-native transformation next year.

1. Salesforce

Salesforce’s Einstein platform has evolved into a larger strategy that connects customer data to generative and predictive models across the CRM stack. The aim is to move beyond suggestions to prescriptive actions that can automate outreach, routing and next-best actions inside workflows.

“We’re already seeing 30% productivity improvements, but it’s not just about code generation,” said Muralidhar Krishnaprasad, president and CTO of Salesforce, earlier in an exclusive interview with AIM, adding that the company is also using AI for test case generation.

Salesforce is also set to acquire Informatica for $8 billion, integrating the company’s AI-powered enterprise cloud data management capabilities, including data integration, governance, cataloguing and MDM. This will strengthen Salesforce’s trusted data foundation and power scalable, safe, and responsible AI across modern enterprises.

2. Atlassian

Atlassian Intelligence, which incorporates AI features, is now integrated into Jira, Confluence and other cloud products, offering drafting, summarisation and contextual prompts that reduce friction in everyday workflows. The firm has made these features generally available and lists AI improvements on its cloud roadmap.

In India, Atlassian’s R&D efforts are driving a new era of innovation, with a focus on developing AI-powered solutions. These include AI-driven service agents, advanced incident management tools and consumption-based billing platforms, fundamentally changing enterprise SaaS operations in an AI-first environment.

Moreover, Atlassian is currently testing Atlassian Studio, a low-code/no-code platform for agent development, designed to enable even users without engineering expertise to create AI agents.

3. HubSpot

HubSpot began rolling out Content Assistant and ChatSpot to integrate AI into marketing and sales workflows. More recently, the company promoted Breeze, an assistant that utilises CRM data and external signals to prepare meeting briefs, generate content and surface strategic insights.

HubSpot’s approach is orchestration, tying content generation, CRM context and analytics together so small and mid-market teams can personalise at scale without stitching multiple point tools. That integration is what could make AI genuinely operational for growth teams relying on HubSpot.

4. Notion

Notion has layered AI features into documents, meeting notes and databases. Summarisation, autofill, and flowchart generation are all offered as native capabilities aimed at turning the workspace into an active knowledge assistant.

The practical result is improved discoverability and reduced cognitive load; teams can extract action items, surface past decisions and spin up project plans from existing notes, making knowledge a live, usable asset rather than static text.

Users are now running their entire workflow with the help of the Notion AI agent. Confluent, at its core, helps Notion scale the AI features.

5. ServiceNow

ServiceNow is setting its Now Assist and agentic AI as part of a platform strategy to embed generative intelligence across IT, HR and customer workflows. The company has strengthened its partnerships with NVIDIA and Hugging Face, contributing to the development of open models.

It is now positioning itself as an AI company by building its own open models, including Apriel 2.0 co-developed with NVIDIA, and embedding multimodal, reasoning-driven intelligence directly into enterprise workflows. Its platform now powers autonomous agents, smarter infrastructure and AI-driven operations across industries, from retail to public services.

With its NVIDIA partnership, Apriel 2.0 launch and strong financials, ServiceNow is signalling what the next phase of enterprise AI looks like: smaller models, bigger results and no waiting around.

At this rate, the only question left is when ServiceNow reaches the $1 billion AI milestone. It might happen faster than anyone expects.

6. Zoho

Zoho has been integrating its in-house LLM, Zia, across its products. Some of the new capabilities follow the launch of Zia Hubs and Zia LLM, Zoho’s proprietary large language model designed for B2B use.

Together, these additions extend Zoho’s AI strategy by making agentic capabilities directly accessible across its ecosystem of over 55 business applications, according to the company.

Because Zoho runs a tightly integrated product portfolio, Zia can act across apps (CRM, finance, workplace) with shared context, a practical operational advantage for customers who want AI to operate cross-product rather than as an isolated feature.

7. Canva

Canva is going AI-native by embedding intelligence across every step of the design journey, with over 13 billion AI feature uses. Its strategy blends in-house models, partnerships with leaders like OpenAI and RunwayML and a growing developer ecosystem, enhancing creativity while keeping human-led design at the centre.

Canva’s Magic Studio, including Magic Design, Magic Media and Brand Kit automation, and Creative OS have turned generative design into a core product capability, enabling rapid generation of templates, videos and brand assets from text prompts. That suite has been expanded through various upgrades to improve the quality of image and video generation.

Canva’s momentum is visible in product milestones. Magic Studio is positioned both for individuals and enterprise teams to scale creative work, shifting labour from manual design to prompt-driven composition and iteration.

The Road Ahead

The next generation of SaaS will likely blur the line between tool and teammate. AI-native platforms won’t just support work, they will participate in it. As models are embedded deeper into product cores, the measure of success will shift from user activity to outcome autonomy.

For software builders, this marks the beginning of a new discipline where they will create systems that can reason, adapt, and self-improve. SaaS, as it seems, is quietly writing its next chapter in the language of intelligence.

Note: The list is in no particular order of ranking and is randomly based on some of the significant AI-focused developments.

The post Top 7 SaaS Platforms Going AI-Native by 2026 appeared first on Analytics India Magazine.

Small IT Firms Show the Only AI Revenue That Actually Matters

Smaller IT firms are outpacing their larger counterparts, generating substantial revenue growth by harnessing AI, data, and process intelligence to deliver faster, outcome-focused solutions.

While these firms derive 40–50% or more of their revenue from AI and data-led services, large IT players like HCLTech report just around 3% of revenue from advanced AI, despite posting $100 million in AI-driven revenue in a single quarter.

EXL’s data and AI-led solutions are driving significant growth, accounting for 56% of the company’s total revenue. The company reported revenue of $529.6 million for Q2FY26, up 12.2% year-on-year, with data and AI-led services growing 18% compared to the same period last year.

Genpact has also seen significant contributions from AI and technology-driven services, with 48% of its total revenue coming from data-tech-AI and its advanced technology solutions business contributing 24% of revenue. Net revenues reached $1.291 billion, marking a 6.6% year-on-year increase.

Anaya Roy of Credibull Capital, a SEBI-registered investment adviser, sees a pattern in smaller companies reporting higher growth. “It has been happening for several quarters now, and it is because they are more agile, their deal durations are much shorter.”

Smaller firms have had a higher chance of renewals rather than long deals, she said, adding that the global uncertainty leads clients to defer their IT spending, but they don’t impact shorter deals.

Among other firms, Happiest Minds Technologies, Firstsource Solutions Ltd and Sonata Software also reported robust growth.

Happiest Minds Technologies reported revenue of $65.1 million for Q2 FY26, up 4.4% year-on-year, and profit after tax grew by 9.1% to ₹5,402 lakhs. The company had set up a generative AI business unit with 22 use cases and a net new sales unit to focus on AI adoption.

Firstsource Solutions Ltd reported consolidated revenue of ₹3,488 million (US$ 524 million) for Q2 FY25-26, up 20.2% year-on-year, with an operating profit margin of 26.2%. The company has been expanding through strategic acquisitions, including the UK-based customer experience outsourcing firm Ascensos, and securing deals in communications, healthcare, and lending sectors.

Sonata Software, meanwhile, reported a 13.5% jump in net profit to ₹120.9 crore, despite a drop in revenue, with AI-led orders forming about 10% of its order book. CEO Samir Dhir highlighted, “As clients accelerate AI-enabled modernisation to enhance competitiveness, we remain confident in the company’s long-term growth trajectory.”

Investors are taking note, with some small IT firms and BPM companies trading at higher P/E multiples than traditional IT companies, reflecting market recognition of the value created through AI-driven services.

The Agility Advantage of Smaller Firms

The competitive edge of smaller IT and BPM firms comes from their ability to respond to evolving client needs faster than larger counterparts, giving them an advantage in AI-led services.

Roy points out that AI has the most immediate relevance in services such as customer service and BPM process intelligence. “They (smaller IT firms) are more agile in the sense that in the current evolving AI environment, they have been able to pass on the benefits of AI productivity gains, and also they are offering better terms,” she added.

“AI has the most use in the current state in such services, like customer service, and anything else which can be replaced immediately by AI falls under what they (companies) offer.”

She said that smaller companies offer pricing terms based on outcomes rather than resources used. They have project-centred teams, rather than hierarchical organisation structures prevalent in bigger companies.

The big firms are trying to adopt the agility of the smaller players, Roy said. “TCS has already laid out plans for data centre investments over the next five to 10 years, and HCL Tech has started reporting AI revenues—it reported $100 million last quarter,” she said.

Roy said that these takeaways from mid-tier and smaller-tier companies are being adopted, but expressed doubts about the agility of the transition given the size and structures of bigger players.

Turning AI and Process Intelligence into Results

Smaller firms are embedding AI and process intelligence into operations to deliver measurable outcomes.

At Genpact, this shift is central to growth. Chief growth officer Riju Vashisht said the company is aware that if it just focuses on automating repetitive processes, it would maintain the limitations of the past, while adding the complexity of the future.

“We move forward through reinvention – and by that, I mean the reinvention of business operations, the reinvention of services and a reinvention of commercial models based on outcomes instead of FTEs.”

She added that Genpact is deliberately moving away from FTE-based models to outcome-based ones. “Already, about 70% of our advanced technology revenues come from non-FTE models, generating more than twice the revenue per headcount compared to our company average.”

Sonata Software is also leveraging AI to grow its order book. Dhir said, “The company closed a large healthcare deal, and AI-led orders formed about 10% of the order book for the quarter. As clients accelerate AI-enabled modernisation, we remain confident in the company’s long-term growth trajectory.”

With AI, data, and platform work becoming central to operations, smaller BPM firms are moving into integrated technology operations—a space traditionally dominated by IT services. The line between IT and BPM is blurring, and winners will be those that can run AI-led operations at scale.

The post Small IT Firms Show the Only AI Revenue That Actually Matters appeared first on Analytics India Magazine.

Why Everyone’s Suddenly Talking About India’s New Data Protection Rules

The central government, on November 14, notified the long-awaited Digital Personal Data Protection (DPDP) Rules, 2025, formally setting in motion India’s multi-stage rollout of a modern privacy regime.

Notably, some of the provisions take effect immediately, most notably the establishment of the Data Protection Board of India (DPBI), headquartered in the National Capital Region (NCR).

Yet, the more profound transformation will unfold gradually over the next 12 to 18 months, as obligations around consent, processing notices, fiduciary responsibilities, and individual rights slowly come into force.

The announcement came after the Business Software Alliance (BSA), an industry body representing global tech giants like Microsoft, AWS, Adobe, IBM, Salesforce and SAP, among others, urged the Indian government to introduce a text and data mining (TDM) exception in copyright law, stressing that it is key to enabling responsible and competitive use of AI across industries.

The announcement also revives a larger question. During public consultation earlier this year, the draft rules received around 9,000 submissions. For a country of 1.4 billion people navigating an increasingly AI-driven digital landscape, does that number signal robust civic engagement or highlight the extent to which citizen awareness is still missing?

“In a country of over 1.4 billion people, expecting every citizen to become an expert on data privacy laws like the DPDP Act is unrealistic. The average person shouldn’t have to dive deep into legal jargon. Citizens should instead be aware of their basic rights and duties in simple terms, three or four key takeaways they can remember and act on. The conversation shouldn’t be about mastering the fine print, but about empowering individuals with the essentials,” said Pawan Prabhat, co-founder of Shorthills AI.

His point underscores that even as India builds one of the world’s most ambitious digital public infrastructures, individuals are still catching up to the fundamentals of data rights. In the age of generative AI, where personal information can be embedded in training sets, inferred by algorithms or profiled at scale, the stakes have never been higher.

But the uncertainty extends beyond citizens. Companies building AI systems face a regulatory landscape that leaves critical gaps unaddressed.

The DPDP Act mandates transparent processing, revocable consent, strong security controls and clearly defined processor contracts. “But the act leaves key AI issues unclear, such as on automated decisions, profiling, model-training uses, sensitive data distinctions, and core processes like consent, deletion, retention and cross-border transfers, creating major accountability gaps,” Srinivas Padmanabhuni, CTO at AIEnsured, told AIM.

While the draft rules attempt to operationalise the act, India is still negotiating the tension between enabling AI innovation and enforcing meaningful privacy protections.

“The establishment of a definite enforcement timeline signals a critical juncture,” said Mayuran Palanisamy, partner at Deloitte India. The rules emphasise breach reporting, verifiable parental consent, consent manager operations, significant data fiduciary criteria and prescriptive safeguards. Successful implementation will require regulators, businesses and consumers to collaborate continuously, and organisations must invest in updated processes, technologies and training to build transparency and integrate privacy into their systems and culture.

Legal experts echo the sentiment by welcoming the clarity, while warning that interpretational guidance will be essential as the rules move from paper to practice.

“The rules offer clear timelines and added flexibility for children’s data, but the real challenge will be delivering scalable, frictionless parental-consent tokens across India’s digital public infrastructure,” said Aparajita Bharti, founding partner at The Quantum Hub.

Children’s data emerges as another critical front in India’s new privacy regime, one where the government has struck a balance between safety, usability and operational flexibility. According to Bharti, the rules now provide the industry a phased compliance roadmap while addressing long-standing concerns around behavioural monitoring, age-appropriate content, parental controls and verifiable consent.

“We welcome these developments. MeitY has provided much-needed clarity and has been judicious in allowing an adequate transition period with major provisions coming into effect 18 months from now,” Shahana Chatterji, partner at Shardul Amarchand Mangaldas & Co, said.

“The industry must now focus on aligning data practices with the Act, and MeitY will need to provide the regulatory and interpretational clarity that will inevitably be needed,” he added.

India is accelerating into an AI-first decade with digital health records, algorithmic credit scoring, predictive governance systems and generative AI woven into daily life. The DPDP Act and its 2025 Rules will become the framework that determines how innovation, rights and accountability coexist.

The next 18 months will define how India interprets privacy in an AI-shaped world at a time when global peers are tightening their own data laws and determining how more than a billion citizens will experience digital agency in the years ahead.

The post Why Everyone’s Suddenly Talking About India’s New Data Protection Rules appeared first on Analytics India Magazine.

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Why Everyone’s Suddenly Talking About India’s New Data Protection Rules

The central government, on November 14, notified the long-awaited Digital Personal Data Protection (DPDP) Rules, 2025, formally setting in motion India’s multi-stage rollout of a modern privacy regime.

Notably, some of the provisions take effect immediately, most notably the establishment of the Data Protection Board of India (DPBI), headquartered in the National Capital Region (NCR).

Yet, the more profound transformation will unfold gradually over the next 12 to 18 months, as obligations around consent, processing notices, fiduciary responsibilities, and individual rights slowly come into force.

The announcement came after the Business Software Alliance (BSA), an industry body representing global tech giants like Microsoft, AWS, Adobe, IBM, Salesforce and SAP, among others, urged the Indian government to introduce a text and data mining (TDM) exception in copyright law, stressing that it is key to enabling responsible and competitive use of AI across industries.

The announcement also revives a larger question. During public consultation earlier this year, the draft rules received around 9,000 submissions. For a country of 1.4 billion people navigating an increasingly AI-driven digital landscape, does that number signal robust civic engagement or highlight the extent to which citizen awareness is still missing?

“In a country of over 1.4 billion people, expecting every citizen to become an expert on data privacy laws like the DPDP Act is unrealistic. The average person shouldn’t have to dive deep into legal jargon. Citizens should instead be aware of their basic rights and duties in simple terms, three or four key takeaways they can remember and act on. The conversation shouldn’t be about mastering the fine print, but about empowering individuals with the essentials,” said Pawan Prabhat, co-founder of Shorthills AI.

His point underscores that even as India builds one of the world’s most ambitious digital public infrastructures, individuals are still catching up to the fundamentals of data rights. In the age of generative AI, where personal information can be embedded in training sets, inferred by algorithms or profiled at scale, the stakes have never been higher.

But the uncertainty extends beyond citizens. Companies building AI systems face a regulatory landscape that leaves critical gaps unaddressed.

The DPDP Act mandates transparent processing, revocable consent, strong security controls and clearly defined processor contracts. “But the act leaves key AI issues unclear, such as on automated decisions, profiling, model-training uses, sensitive data distinctions, and core processes like consent, deletion, retention and cross-border transfers, creating major accountability gaps,” Srinivas Padmanabhuni, CTO at AIEnsured, told AIM.

While the draft rules attempt to operationalise the act, India is still negotiating the tension between enabling AI innovation and enforcing meaningful privacy protections.

“The establishment of a definite enforcement timeline signals a critical juncture,” said Mayuran Palanisamy, partner at Deloitte India. The rules emphasise breach reporting, verifiable parental consent, consent manager operations, significant data fiduciary criteria and prescriptive safeguards. Successful implementation will require regulators, businesses and consumers to collaborate continuously, and organisations must invest in updated processes, technologies and training to build transparency and integrate privacy into their systems and culture.

Legal experts echo the sentiment by welcoming the clarity, while warning that interpretational guidance will be essential as the rules move from paper to practice.

“The rules offer clear timelines and added flexibility for children’s data, but the real challenge will be delivering scalable, frictionless parental-consent tokens across India’s digital public infrastructure,” said Aparajita Bharti, founding partner at The Quantum Hub.

Children’s data emerges as another critical front in India’s new privacy regime, one where the government has struck a balance between safety, usability and operational flexibility. According to Bharti, the rules now provide the industry a phased compliance roadmap while addressing long-standing concerns around behavioural monitoring, age-appropriate content, parental controls and verifiable consent.

“We welcome these developments. MeitY has provided much-needed clarity and has been judicious in allowing an adequate transition period with major provisions coming into effect 18 months from now,” Shahana Chatterji, partner at Shardul Amarchand Mangaldas & Co, said.

“The industry must now focus on aligning data practices with the Act, and MeitY will need to provide the regulatory and interpretational clarity that will inevitably be needed,” he added.

India is accelerating into an AI-first decade with digital health records, algorithmic credit scoring, predictive governance systems and generative AI woven into daily life. The DPDP Act and its 2025 Rules will become the framework that determines how innovation, rights and accountability coexist.

The next 18 months will define how India interprets privacy in an AI-shaped world at a time when global peers are tightening their own data laws and determining how more than a billion citizens will experience digital agency in the years ahead.

The post Why Everyone’s Suddenly Talking About India’s New Data Protection Rules appeared first on Analytics India Magazine.

Why Everyone’s Suddenly Talking About India’s New Data Protection Rules

The central government, on November 14, notified the long-awaited Digital Personal Data Protection (DPDP) Rules, 2025, formally setting in motion India’s multi-stage rollout of a modern privacy regime.

Notably, some of the provisions take effect immediately, most notably the establishment of the Data Protection Board of India (DPBI), headquartered in the National Capital Region (NCR).

Yet, the more profound transformation will unfold gradually over the next 12 to 18 months, as obligations around consent, processing notices, fiduciary responsibilities, and individual rights slowly come into force.

The announcement came after the Business Software Alliance (BSA), an industry body representing global tech giants like Microsoft, AWS, Adobe, IBM, Salesforce and SAP, among others, urged the Indian government to introduce a text and data mining (TDM) exception in copyright law, stressing that it is key to enabling responsible and competitive use of AI across industries.

The announcement also revives a larger question. During public consultation earlier this year, the draft rules received around 9,000 submissions. For a country of 1.4 billion people navigating an increasingly AI-driven digital landscape, does that number signal robust civic engagement or highlight the extent to which citizen awareness is still missing?

“In a country of over 1.4 billion people, expecting every citizen to become an expert on data privacy laws like the DPDP Act is unrealistic. The average person shouldn’t have to dive deep into legal jargon. Citizens should instead be aware of their basic rights and duties in simple terms, three or four key takeaways they can remember and act on. The conversation shouldn’t be about mastering the fine print, but about empowering individuals with the essentials,” said Pawan Prabhat, co-founder of Shorthills AI.

His point underscores that even as India builds one of the world’s most ambitious digital public infrastructures, individuals are still catching up to the fundamentals of data rights. In the age of generative AI, where personal information can be embedded in training sets, inferred by algorithms or profiled at scale, the stakes have never been higher.

But the uncertainty extends beyond citizens. Companies building AI systems face a regulatory landscape that leaves critical gaps unaddressed.

The DPDP Act mandates transparent processing, revocable consent, strong security controls and clearly defined processor contracts. “But the act leaves key AI issues unclear, such as on automated decisions, profiling, model-training uses, sensitive data distinctions, and core processes like consent, deletion, retention and cross-border transfers, creating major accountability gaps,” Srinivas Padmanabhuni, CTO at AIEnsured, told AIM.

While the draft rules attempt to operationalise the act, India is still negotiating the tension between enabling AI innovation and enforcing meaningful privacy protections.

“The establishment of a definite enforcement timeline signals a critical juncture,” said Mayuran Palanisamy, partner at Deloitte India. The rules emphasise breach reporting, verifiable parental consent, consent manager operations, significant data fiduciary criteria and prescriptive safeguards. Successful implementation will require regulators, businesses and consumers to collaborate continuously, and organisations must invest in updated processes, technologies and training to build transparency and integrate privacy into their systems and culture.

Legal experts echo the sentiment by welcoming the clarity, while warning that interpretational guidance will be essential as the rules move from paper to practice.

“The rules offer clear timelines and added flexibility for children’s data, but the real challenge will be delivering scalable, frictionless parental-consent tokens across India’s digital public infrastructure,” said Aparajita Bharti, founding partner at The Quantum Hub.

Children’s data emerges as another critical front in India’s new privacy regime, one where the government has struck a balance between safety, usability and operational flexibility. According to Bharti, the rules now provide the industry a phased compliance roadmap while addressing long-standing concerns around behavioural monitoring, age-appropriate content, parental controls and verifiable consent.

“We welcome these developments. MeitY has provided much-needed clarity and has been judicious in allowing an adequate transition period with major provisions coming into effect 18 months from now,” Shahana Chatterji, partner at Shardul Amarchand Mangaldas & Co, said.

“The industry must now focus on aligning data practices with the Act, and MeitY will need to provide the regulatory and interpretational clarity that will inevitably be needed,” he added.

India is accelerating into an AI-first decade with digital health records, algorithmic credit scoring, predictive governance systems and generative AI woven into daily life. The DPDP Act and its 2025 Rules will become the framework that determines how innovation, rights and accountability coexist.

The next 18 months will define how India interprets privacy in an AI-shaped world at a time when global peers are tightening their own data laws and determining how more than a billion citizens will experience digital agency in the years ahead.

The post Why Everyone’s Suddenly Talking About India’s New Data Protection Rules appeared first on Analytics India Magazine.