Walter Adamson

🇦🇺 AI Impact Navigator: A Guide for Responsible AI Implementation - The Australian Government Department of Industry, Science and Resources, National Artificial Intelligence Centre and CSIRO have released a new guide to help businesses navigate the impacts of artificial intelligence (AI). The AI Impact Navigator is a framework for companies to use in assessing and measuring the impact and outcomes of their use of AI systems. It provides a way for company leaders to communicate and discuss what's working, what they've learned, and what their AI impact is. The Navigator is structured around 4 dimensions to help you leverage AI for positive impact: 💠 Effective AI and community impact   💠 Customer experience and consumer rights   💠 Workforce and productivity   💠 Social licence and corporate transparency   🔗 Find more information here 👉 https://lnkd.in/gN3DbkAs

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Had a great chat about the future trends and what's shaping business in 2024 and beyond in forecasting futures with the folks over at MBA Discovery From AI, to sustainability, an ageing population and geopolitical shifts. Check it out here - and feel free to share what you think? https://lnkd.in/gq6j-yDy

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In breaking news, smaller consultancies are responding to cheap AI offerings from the big end of town by offering "human based services to clients". Source: The Australian 6th January 2025.

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Did you know that Australia is the home of 2.3% of the world's tech unicorns ($1b plus valuation companies). Deep tech is clear strength of Australia and it is why Japanese corporates are looking at Australia. The Australian Japan Business Cooperation Committee (AJBCC) is lifting the lid on what is driving Japanese businesses and Australian startups. If you are interested, then this webinar could be for you. Richard Andrews, Cristina Merino Ishizuka, Jonathan Raju, Annie Jiang, Emily Doran, Takero Izuhara, Tim Mclennan, Ken Jefferd, Invest Victoria

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Want your machine learning project to qualify as core R&D Tax Incentive? Focus on experimenting with new algorithms or tackling unknown technical challenges? The AusIndustry looks for projects that involve systematic efforts to overcome uncertainty, not just applying known methods. https://lnkd.in/g6FuuZ3B.

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Overwhelmed with the sheer number of #GenAI / #LLM usecases that are bubbling up in your enterprise? Have a read of this whitepaper and come and chat to us. Thomas Maas James Wilson Emma Bromet Kathryn Collier James Hayes Marty Conneely Brett Thebault

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Thanks ITBrief for the coverage Climate & Decisions #ESG #Climate #DigitalTransformation

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Lots of organisations are trialling Microsoft Copilot, but few share the results. Vendors provide glowing case studies, but what about the mixed ones? That’s why I was excited to see a public study from the Office of Digital Government Western Australia. It was more nuanced than the usual rose-tinted vendor stories, offering valuable insights into AI adoption, raising questions about implementation strategies the rest of us can learn from 5,765 licenses deployed: solid sample size for a robust trial 33% adoption rate: Decent for a new, little-understood workplace technology, but hardly transformative The primary use? Summarising meetings & drafting—important but isolated tasks that lack the integration needed for broader impact. Copilot is doing work that might otherwise not get done, but it’s not yet the game-changer AI could be Observations: Limited integration: Meeting summaries and drafts are isolated activities. Without connecting tools to broader workflows, the potential for transformative value is lost Lack of process analysis: A comprehensive process review was recommended but appears not to have been done. Dropping tools into workflows without context limits ROI Adoption gaps: Why did only 33% adopt when meetings are universal? Barriers—technical, cultural, or support-related—likely played a role Training matters: People who undertook more than one type of training (eg workshops, peer learning, self-paced modules) showed much higher adoption rates. Varied, ongoing training is essential to building confidence and capability Technical limitations: Issues with Excel & Outlook and inaccuracies hurt productivity. Familiarity bias toward enterprise platforms like Microsoft might not always serve users best Prompt engineering struggles: Challenges with prompts suggest gaps in training or change management rather than tool design Over-reliance risks: Concerns about losing deep knowledge are valid. Organisations must balance efficiency with accountability and critical thinking Early adopter bias: Early users were perceived as more productive, which may foster resistance or fear—a common hurdle in change management If you’re planning a trial: Invest in varied training: Training shouldn’t be a one-off. Use diverse formats and reinforce adoption over time Choose fit-for-purpose tools: Don’t default to familiar vendors. Smaller, more agile tools can often deliver better results Conduct a discovery phase: A thorough process review ensures tools align with organisational needs, reducing risks and maximising ROI Set clear metrics: Measure costs, benefits, and adoption outcomes to guide experimentation and ensure accountability If your organisation is running a Copilot trial, or considering one, these steps can help you maximise success. And of course, you can always come talk to us at Lithos Partners. You knew that, right? Have you worked with AI tools like Copilot? I’d love to hear your experiences or tips for successful adoption.

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Thanks to Kirsten (KP) Patterson, David Downs and Anna Campbell from the Institute of Directors in New Zealand on their reflections and lessons for #governance #directors from the Spark AI* Mini-MBA. Here is my favorite thought on how we should use #generative AI: Treat #AI like a 'high performing graduate'. It has a good base level of knowlege, needs adult supervision in the office, needs to be fact checked, needs good context and requests, your communication will determine it's responses and it will not always perform consistently. Let me know your thoughts on this take. Here are some more of my main takeaways: We have previously talked about an extending digital divide, and we may be seeing an AI class of leaders developing, with some being left behind. As Generative AI is new to a lot of people, many feel they are 'lurkers' - interested but not engaging or not knowing how to engage. You have permission to engage with AI, there is no one that is going to give you an endorsement or permission to explore and learn. Most directors and management are learning about AI together, at the same time. There is room to be an interested learner. Being a learner is key cornerstone of ongoing good governance. There is value in using AI as a "strategy companion", moving past the gimmicky uses of AI that most people engage with. For example in the images there is a clear divide in the depth of use of AI. Understanding the protection of sensitive and private information, AI should be looked at as a significant productivity tool for organizations. David shared a matrix of different uses: - Low risk / Low effort: Email drafting and responses Basic note taking Simple task management Information retrieval - Low effort / High risk: Basic sentiment analysis on public opinion Automated document reviews - Low risk / High effort: Personalised learning and development Advanced meeting summaries Automated report generation Smart scheduling assistance - High effort / High risk: Strategic planning ideas Comprehensive personal knowledge management Enhanced decision support Intelligent virtual assistance AI can help creativity, stimulating and prompting ideas. It can also help with more mundane decisions, allowing space for more intentional thought of complex issues. AI is often thought of as a technological tool, but this can be a limiter on how we can use it, personally as leaders and professionally as organizations. You can start prompts with a caveat, 'I want facts, validate and quote the source of information, and no generated or hallucinated information'. You can also also add these sorts of directions into ChatGPT settings, have a look in the cog icon. This can be a brilliant tool for neuro diverse people, as it can take a large amount of verbal information, and summarize this. There are some things that AI will be an expert on, such as getting AI to write a draft policy on AI use. *I have used AI in this post to refer to Generative AI.

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The National AI Centre and Fifth Quadrant have just released their report: Australian Responsible AI Index 2024. This report serves as a timely reminder on the importance of leadership, revealing a correlation between business leadership involvement and responsible AI maturity. Importantly, it also shows that there's still a significant gap between what organisations say they do and what they actually do. A factor that I attribute to a skills gap. This underscores the growing importance education and training will play in helping to drive responsible AI adoption across Australia. I was glad to emphasise this point during my recent talk on ethical AI at a recent ACS (Australian Computer Society) event. Codex have had the privilege of working with organisations of all sizes in Australia to help them embark on their AI journey in a responsible and sustainable way. If you're looking to leverage AI in your business, but aren't sure where to start, we're here to help. #AI #EthicalAI #ResponsibleAI #ML #MLOps https://lnkd.in/gctdst_h

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Nice framework for the network effect of AI beyond chipsets by my former colleague and fellow analyst Daniel Newman. This shows how the exuberance in the chipset AI market can waterfall and positively impact virtually all industries. 🙌

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🚀 Generative AI: Top Priority for Aussie Execs New Salesforce research reveals: 🎈 81% of Australian C-suite execs rank #GenAI in top 3 business priorities 🎈 50% have a clear strategy, 🎈 42% developing one Great stats and all driven by the understanding that GenAI will drive enhanced productivity, innovation, and competitive edge They also recognise some common challenges such as 🎳 Data accessibility & inclusivity 🎳 AI accuracy 🎳 Incomplete data for AI training 🎳 Data privacy & security We have found from the GenAI apps we have deployed that all of these challenges can be overcome with the right approach enabling us to successfully unlock GenAIs true potential for business impact, check out DeeperAutomation.AI Are you ready for the AI revolution? https://lnkd.in/eJJEM7EF).

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Generative AI: Calculating Business Value Amidst Uncertainty As the initial excitement around generative AI (GenAI) begins to wane, Australian executives are eager to see returns on their investments. However, many organisations are grappling with the challenge of proving and realising the value of this technology. The financial implications of developing and deploying these models are becoming increasingly apparent as initiatives expand. Gartner predicts that by 2025, at least 30% of GenAI projects will be abandoned after the proof of concept stage due to escalating costs, unclear business value, poor data quality, or inadequate risk controls. While piloting is relatively straightforward and cost-effective, scaling presents significant challenges. The uncertainty in predicting costs and value upfront makes it difficult for organisations to justify substantial investments, particularly when it comes to productivity enhancements that don't directly translate to financial benefits. Some key points to consider: 1. Deployment costs can be significant, depending on use cases and scale 2. There's no one-size-fits-all approach to generative AI implementation 3. Organisations need to identify their AI ambition, whether it's market disruption, conservative productivity gains, or industry transformation 4. Generative AI requires a higher tolerance for indirect, future financial investment criteria rather than immediate ROI Early adopters across various industries report average improvements of 15.8% in revenue increase, 15.2% in cost savings, and 22.6% in productivity. However, it's crucial to note that these benefits are highly specific to individual companies, use cases, roles, and workforce compositions. To maximise the potential of generative AI, organisations should: 1. Collaborate with HR, finance, legal, and corporate strategy teams early in the process 2. Consider long-term benefits, such as improved customer engagement and reduced employee burnout 3. Establish fast-cycle innovation labs to assess both technical feasibility and proof of value 4. Regularly analyse business value and total costs to make informed investment decisions As we navigate the complexities of generative AI implementation, it's clear that success lies in strategic planning, cross-departmental collaboration, and a willingness to look beyond immediate financial returns. #GenerativeAI #BusinessValue #AIStrategy #TechInvestment Read more: https://lnkd.in/e-Z7R33X

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We hear you Adam Mercer and Datacom… and totally agree that upgrading hardware & software can spark compelling growth:  https://bit.ly/3yBabFe Too often we come across companies that hang on to outdated – and no longer supported – technology, therefore increasing risks, inefficiencies and costs. An example in case is mentioned here: https://bit.ly/3V0Tr1N

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This so-called ‘report’, published by industry lobby group Tech Council of Australia, a group funded by the AI tech companies and seemingly supported by a Federal minister, seems to be completely at odds with other reports that provide compelling findings that #AI will result in the widespread loss of jobs. Sure, AI may *create* some jobs, however the jobs that will be *lost* due to AI will far exceed in number the ones created (best case scenario is that for every job lost as a result ot AI, AI will only create 0.9 jobs. Heres a few contradictory reports that will debunk the findings of this document: - Labour hire firm Adecco says that 41% of those in the C-suite expect to employ fewer people because of AI - https://lnkd.in/g7pFmfab - According to Resume Builder, more than 1/3rd of business leaders said that AI replaced workers in 2023. - Elon Musk believes that AI will get to a point where ‘no job is needed’ with AI set to become ‘the most disruptive force in history’. - AI could eliminate 8 million jobs in the UK, with women and early careet workers most vulnerable according to McKinsey & Company https://lnkd.in/grk3y33m. As a technologist who has been playing with, hacking into and messing with tech since I took apart a phone aged 5 (and seriously upset his dad), I say with absolute certainty that the topic of AI will become the biggest public policy issue for governments to deal with in the next 20 years. Heres what I would like to see answered in an AI report: - how will governments fund the looming need to fund social welfare needed for retraining, redeployment and unemployment - how will governments mitigate from what could likely turn into significant social unrest as a result of not enough employment opportunities. - how will AI companies fund (though effective taxation) these social programs - how will governments and societies, including the poorest to the richest, enjoy the benefits of the AI boom - how will the concentration of wealth towards big tech be managed.

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🤔 What does “𝒎𝒆𝒂𝒏𝒊𝒏𝒈𝒇𝒖𝒍” really mean in “meaningful human oversight” when it comes to GenAI? How can humans oversee something they don’t fully understand? What are the approaches? It was a pleasure to explore these questions in my talk earlier today at the GenAI Summit Sydney. I debunked a few common myths—like “human-in-the-loop solves everything,” “AI are just tools, humans make the decisions,” and “AI-augmented intelligence.” I introduced CSIRO's Data61 approach to design-time oversight—ensuring human agency and oversight are properly embedded in GenAI—and runtime oversight through guardrails and system-level understanding, rather than just model-level understanding. Find more here https://lnkd.in/gPhid9tX Here are a few selected slides highlighting the key messages.

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Australia rises six spots in the IMD World Competitiveness Ranking, a definitive resource for understanding the global economic landscape. Australia now places 13th out of 67 economies evaluated. IMD share “Australia continues to excel thanks to our effective legal environment, policy stability and predictability, reliable infrastructure, and skilled workforce. To continue to strengthen our position, we must proactively seize the opportunities that 2024 presents, such as: 🌎 Advancing Clean Energy 💪 Revitalising Productivity 💚 Expanding social and economic participation You can delve into the specifics of the ranking here: https://lnkd.in/gFp-CzWD Looking forward to IMD’s Australia Mangement Transformation Forum tomorrow! Greg Campbell Rich Hirst #australia #competitiveness #transformation

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