Artificial intelligence is moving from promise to practice across senior living, with organisations reporting growing optimism alongside practical constraints. Recent survey data indicates that leaders now view AI as a positive force for managing communities and many have begun deploying tools for analytics, engagement and operational support. Adoption is tempered by uneven organisational competency, a continuing focus on culture change and a clear recognition of risks. Sessions highlighted real deployments, early benefits in marketing, sales and cybersecurity, and the increasing use of large language models (LLMs) for productivity. Alongside this momentum sits a strong emphasis on data governance, training and human oversight to ensure resident safety and responsible implementation.
Adoption Climbs Across Analytics, Engagement and Operations
Leaders are increasingly confident in AI’s role in senior living. According to the 2025 Argentum Technology Report, 76% of surveyed leaders expect AI to be a transformative or positive force in managing senior living communities over the next five years, up from 58% in 2023. Reported deployments centre on operational value. Most organisations use AI and machine learning in predictive analytics at 70%. Marketing and sales efficiencies follow at 50%, matched by the use of chatbots for resident interaction at 50%. These areas reflect early, measurable gains that align with immediate organisational priorities, from forecasting to occupancy growth and resident communication.
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The prominence of AI at the LeadingAge Annual Meeting reinforces this uptake. Multiple sessions examined the continuing adoption of AI, including an interactive discussion that integrated an LLM as a panel participant to demonstrate real-time synthesis of sector reports and context for the audience. The discussion underscored how senior care providers are moving beyond exploration toward targeted use cases that can improve daily workflows.
Skills, Tools and Enterprise Readiness
Despite growing activity, enterprise-level capability is still developing. Insights shared from a CTO Hotline survey indicated that no organisations reported extensive AI competency. Most respondents characterised their status as very limited AI knowledge or having certain team members with competency. Confidence to deploy remains cautious, with 49% feeling somewhat ready to implement targeted AI. This mixed picture suggests that while pilots and discrete solutions are advancing, broader organisational maturity and skills remain a work in progress.
LLM adoption is expanding across the sector, with a clear leader among workplace tools. Respondents reported strong uptake of Microsoft Copilot at 63%, followed by 36% using ChatGPT, 3% using Google Gemini and 1% using Claude. Among those not yet using an LLM, 53% plan to implement one within the next 12 months. The pattern points to a pragmatic approach: organisations are layering generative capabilities onto existing productivity environments while experimenting with alternative models for specific needs. Leaders also stressed the centrality of data to generative performance, noting that effective use depends on reliable, well-structured and contextually relevant information.
Culture change featured prominently in the discussion of readiness. Organisations are working to move teams from basic AI literacy to practical fluency so that new tools can be adopted with confidence and consistency. Examples included using generative platforms to create engaging onboarding content, positioning AI as an enabler for learning and alignment rather than a disruptive add-on.
Early Benefits, Governance Priorities and Security Vigilance
Operational use cases are emerging across clinical, sales and marketing workflows. Teams are testing LLM-enabled assistants to accelerate routine tasks, summarise information and standardise outputs. In parallel, cybersecurity platforms that incorporate AI are improving visibility and response by surfacing anomalous activity more quickly, such as unusual login patterns that may otherwise go unnoticed. These examples illustrate how AI can enhance both front-line operations and back-office resilience when integrated into existing systems.
Alongside practical gains, leaders consistently elevated governance and safety. Discussions highlighted the need to maintain human oversight in areas that rely on empathy and nuanced judgement, particularly in resident care planning. Data privacy and bias were cited as ongoing risks, especially if tools are deployed without adequate safeguards or if training data does not reflect resident populations. The message was clear: keep humans in the loop, apply robust data protections and routinely review outputs for fairness and accuracy.
Education is a parallel priority. As AI-assisted phishing attempts rise, organisations are investing in continuous training to strengthen workforce awareness and incident response. This focus links back to enterprise readiness: technology alone is insufficient without clear policies, reliable data practices and staff who understand both the benefits and the limits of AI systems.
Senior care organisations are advancing AI adoption where the benefits are most immediate, particularly in predictive analytics, marketing, sales and resident engagement, while extending protections through governance, oversight and training. Enterprise competency is developing, with uneven skills offset by growing use of workplace-integrated LLMs and careful, targeted deployments. The sector’s trajectory points to steady integration of AI into daily operations, underpinned by attention to data quality, privacy and security. The near-term task for healthcare leaders is to pair measured expansion of AI use cases with the structures that ensure safety, equity and sustained value for residents and staff.
Source: HealthTech
Image Credit: iStock
