NeoCai

AI increasingly drives decisions that affect companies and employees and how they operate up to now. Decision-making and business analytics are transforming in an overwhelming level the current status quo. Evaluating the business and moral dimensions of AI implementations into the business's future strategy is crucial for success and retaining both results and the well-being of your team. NeoCai offers the best hands-on practices from the Silicon Valley teams that already have strategized and executed.

Working with C-Suite executives to optimize the company's A.I. strategy for the future, focusing on organizational change management (O.C.M.) regarding structure, management, and operations. Co-operating with established firms across the U.S. & EMEA and with Scaleups & V.C.s in Silicon Valley to identify options for the organization, suggest recommendations for change, and advise on additional resources to implement solutions.

Founder & Principal

Powerside

Strategically led a team in developing global strategic customer acquisitions and new alliances. Proactively identified new target markets, captured key accounts despite the pandemic & delivered outstanding results QoQ for both direct sales & indirect. Fostered the development of a culture of success & accountability by leading cross-functional teams.  

Converted sales and business development operations and turned around poor performance/results. Installed new strategies and processes that achieved ten quarters in a row above target and 56% year-over-year revenue growth. Successfully entered new vertical markets and geographical territories by winning a significant market share. 

Indicative sectors: Semiconductors, Energy Grid, Utilities, Datacenters, Medical Devices & Hospitals, E.V. Cars & Charging Stations, Renewables (Solar, Wind), High-Tech, B2B Electronics

Vice President of Global Enterprise Sales, Business Development, & Strategic Alliances

PowerCET

Managed and executed the M&A of PowerCET from Sonel. Branded a new organization for the U.S. market and implemented strategic alliances so the new entity (SonelTest) could become a well-known player in the U.S. and LATAM markets.

Executive Vice President

mantis.group

Served several leadership roles in the U.S. and the E.U., selling Enterprise SaaS & IoT S.C.M. and logistics software and solutions and servicing large enterprises in North and South America. Transformed startup into a global group of companies with recognition from Gartner as an SCM global leader which led to successful M&A with Ecovium Group.

Managing Director (North & South America)

During the "Euro-debt" crisis, successfully led and navigated the company against all odds to become a leader in  SCM SaaS/IoT solutions for large enterprises all across central and northern Europe. Developed from scratch VARs, strategic alliances, and significant high-level KA customers in every country & and business channel that was available at the time.

Managing Director (Central & Northern Europe)

Spearheaded client acquisition, contracting, and retention efforts for the company's operations in EMEA.
Administered $MM in revenue earned from industry-leading customers. Navigated the expansion across the EU and MENA.

International Business Development, Sales, & GTM Director

Groupe Renault

Responsibilities:
Management:
·	Coordinating the works performed by the sales team
·	Recruiting, training and inducting new employees 
Sales development strategies:
·	Analyzing whether it is possible to make use of market niches for car part sales maximization
·	Recommending optimization activities in production and logistics

International Business Development Manager

Responsibilities:
Project management:
·	Coordinating key implementation project
·	Setting milestones and monitoring their execution
·	Building relationships with project stakeholders 
·	Managing project changes

Business Development

Greek Army

Private/Soldier (Artillery). Honorable Discharge.

Private

Business Development & Sales | Global Strategic Alliances, GtM, & Partnerships | AI, SaaS, IoT, Robotics, & Services | Startup & Scaleup | 73% Company Growth in 9Q | Customer Centric | Multicultural Builder | MBA & MSc.

Executive with full P&L responsibility of international multi-site SaaS/IoT $MM businesses and cross-functional/multicultural FTEs/Teams across North America, Europe, and Asia for Silicon Valley & European PE/VC funded startups.

Managing startups, business transformations, and complex multi-site international businesses while based in the EMEA and the US. Successes include Enterprise SaaS startups and automation/Robotics, Energy Grid/Renewables IoT, business turnarounds, organization restructuring, and industry 4.0 transformations.

Identifying new business opportunities, cultivating and maintaining relationships with executive business partners, and spearheading effective sales and market penetration strategies positions me to impact your organization significantly. By leveraging expertise and insight to implement forward-thinking and strategic business development solutions, I excel at connecting with key decision-makers and quickly building profitable, lasting partnerships that scale growth. Marketing, Go-to-Market, Global Business Development, Channel/VARs, Strategic Alliances, Customer Experience (Cx) step-changes, product launches, macroeconomics crisis recovery, and executing global mergers and acquisitions (M&A) through selection – due diligence – negotiation – integration, and performance improvement.

Hands-on experience leading SaaS/IoT businesses across the e-Mobility, Semiconductor, Energy, Utilities, EV Infrastructure, DataCenters, Medical/Diagnostics OEMs, Transportation & Logistics, and C&I.

Dual Citizenship USA and EU/GR

𝗔𝗜 𝗮𝗻𝗱 𝘁𝗵𝗲 𝗻𝗲𝗲𝗱 𝗳𝗼𝗿 𝘁𝗵𝗲 "𝗺𝗮𝗺𝗺𝗼𝘁𝗵 𝗶𝗻 𝘁𝗵𝗲 𝗿𝗼𝗼𝗺" (𝗮.𝗸.𝗮. 𝘂𝘁𝗶𝗹𝗶𝘁𝗶𝗲𝘀) 𝘁𝗼 𝗲𝗺𝗲𝗿𝗴𝗲 𝗳𝗿𝗼𝗺 𝘁𝗵𝗲 "𝗜𝗰𝗲 𝗔𝗴𝗲" 𝗮𝘀 𝘀𝗼𝗼𝗻 𝗮𝘀 𝗽𝗼𝘀𝘀𝗶𝗯𝗹𝗲. 

According to Bloomberg, utility companies are bracing for historic spikes in electricity demand in the US, driven by #datacenters and #artificialintelligence. What is the big problem with artificial intelligence? It takes a tremendous amount of energy to build and operate. And utilities have a part in that. The need for power from data centers has always been enormous, but after the hoopla surrounding AI, that demand increased dramatically.

When data center operators choose where to build, #energy availability is a significant factor. Usually, after discussing their power requirements with a local #utility, the utility requests permission to construct a new plant or purchase electricity from outside sources. The Georgia Public Service Commission recently granted Georgia Power permission to increase its capacity by 1.4 gigawatts to meet the demand from data centers and other commercial enterprises. Storage and renewable energy are significant enablers to satisfy this rising demand.

#Utilities benefit significantly from this surge in demand because of #AI, provided they can generate sufficient electricity to meet it. However, a growing concern is that the US electricity grid may not be adequately prepared for this impending wave. This presents a unique opportunity for utilities to adapt and innovate, with some investors now focusing on the businesses that will be instrumental in fortifying the #energygrid, enabling utilities to thrive in this new, high-energy climate.

Spyridon Georgiadis

What is the importance of fortifying the energy grid?

How do data centers impact electricity demand?

𝗧𝗵𝗲 𝗰𝗼𝗻𝘃𝗲𝗿𝗴𝗲𝗻𝗰𝗲 𝗼𝗳 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀, 𝗔𝗜, 𝗜𝗼𝗧, 𝗮𝗻𝗱 𝗗𝗶𝗴𝗶𝘁𝗮𝗹 𝗧𝘄𝗶𝗻𝘀. 𝗦𝘁𝗮𝗿𝘁 𝗲𝗺𝗯𝗿𝗮𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝘁𝗼𝗱𝗮𝘆 (𝗳𝗶𝘃𝗲 𝘆𝗲𝗮𝗿𝘀 𝗳𝗿𝗼𝗺 𝗻𝗼𝘄 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝗮 𝗯𝗶𝘁 𝘁𝗼𝗼 𝗹𝗮𝘁𝗲) 

American manufacturing organizations have made significant investments in increasing #automation: By 2023, 44,303 industrial #robots were added to production and logistics, A 12% increase from the previous year. According to IFR's research, the electrical and electronics industries are the next-largest adopters.  The manufacturing sector in the US is still the most developed in the world. But what is the future regarding merging #RPA, #AI, #IoT, and #Digitaltwins so these investments can achieve the highest possible #ROI?

According to a Robocorp survey from 2022, 69% of the companies that claim to have implemented RPA report having at least one automated procedure go wrong every week (personal experience after twenty years in the industry: once per month, still sounds about right!), with many of these issues taking hours to resolve. However, the emergence of #generativeAI offers a glimmer of hope. Without hastening the demise of RPA platforms, generative AI may be able to determine many of these problems. RPA manufacturers believe that generative AI-powered agents and RPA can coexist harmoniously and grow to complement one another. 

With generative #artificialintelligence (#GenAI), RPA platforms can become more capable of comprehending and producing natural language, automating content generation, making better decisions, and even producing code. RPA platforms may enhance customer value, boost productivity and efficiency, and broaden their use cases and applications by including generative AI models. Thousands of businesses widely use #RPA platforms and will be willing to be used for agents with generative AI. RPA has expanded in part because of its ease of integration with current work patterns through AI integration, and this will continue to be beneficial for increasingly intelligent agents in the future.

Every customer in every industry has seen an exponential improvement in their capacity to employ generative AI to automate many more use cases. Integrating generative AI into intelligent automation technologies, such as RPA, not only presents an opportunity for businesses to save expenses and boost output but also a necessity to stay competitive. Businesses that don't use these technologies will find it increasingly difficult to compete with those that do.

What impact does AI integration have on RPA platforms?

What is the significance of automation in the manufacturing sector?

How can generative AI enhance RPA platforms?

𝗪𝗵𝗶𝗹𝗲 𝗹𝗮𝘀𝘁𝗶𝗻𝗴 𝗹𝗼𝗻𝗴𝗲𝗿 𝘁𝗵𝗮𝗻 𝗶𝗻 𝗽𝗿𝗲𝘃𝗶𝗼𝘂𝘀 𝗱𝗲𝗰𝗮𝗱𝗲𝘀, 𝘁𝗵𝗲 𝗰𝘂𝗿𝗿𝗲𝗻𝘁 𝗱𝗼𝘄𝗻𝘁𝘂𝗿𝗻 𝗶𝗻 𝗦𝗮𝗮𝗦 𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻𝘀, 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲𝘀, 𝗮𝗻𝗱 𝗠&𝗔𝘀 𝗶𝘀 𝗮 𝘁𝗲𝘀𝘁 (𝗮𝗻𝗱 𝗮𝘁 𝘁𝗵𝗲 𝘀𝗮𝗺𝗲 𝘁𝗶𝗺𝗲, 𝗮 𝘁𝗲𝘀𝘁𝗮𝗺𝗲𝗻𝘁) 𝘁𝗼 𝘁𝗵𝗲 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆'𝘀 𝗿𝗲𝘀𝗶𝗹𝗶𝗲𝗻𝗰𝗲. Even the recessions of 2008 and 2016, which were significantly more severe, were relatively brief. The 2008–2009 SaaS downturn, during which the world economy nearly collapsed, was also shorter than anticipated. SaaS returned sooner than we thought in hindsight. This current downturn, which began in late 2021, is now in its third year, but I remain steadfast in the sector's ability to navigate it. 

Revenue multiples are roughly as low as they have been since 2017, rather than only slightly below the "party time" of 2021's peak. This decline in multiples and SaaS growth has, in many respects, contributed to an uncontrollably high increase in AI #VC funding. AI is the portion of #B2B separated from the remainder of the SaaS cycle. Its enthusiasm and OpenAI's phenomenal top-line growth demonstrate that enormous rewards are possible. Here are a few suggestions from SaaStr (the images as well) for the upcoming period: 

Initially, focus entirely on helping your clients achieve real efficiency gains. With #ROI calculators and other tools, we have always pretended that business software is efficient. The moment has come actually to do it. Get this right.

At the very least, achieve a minimum AI-friendly concept. Does modern AI miraculously transform every category? Perhaps not. Is #AI lacking in specific #SaaS components? Perhaps. Customers, however, always desire increased efficiency from the hype, and AI is that right now. There is a great deal of momentum. At the very least, don't lose deals because this situation hasn't competitive parity.

Close each customer and be flexible to get them onboard "yesterday." Does that imply a less expensive version? Try it. Does it imply offering your free version even more of it? Please do it. Does that mean that people should downgrade rather than move on? Execute it. Does that imply that potential customers may choose not to be part of your template "pipeline" process? Please don't make them, then. The most crucial thing is to add 20%–50% more new clients annually. That's what lies ahead for you.

Increase utilization more quickly than income. Increasing revenue is what counts. However, if utilization isn't increasing quicker than income, things aren't looking good for you in the long run. Select the top one to three usage #KPIs and ensure that their growth rate exceeds that of revenue. 𝗧𝗵𝗶𝗻𝗸 𝗹𝗶𝗸𝗲 𝗮 𝗵𝘂𝗻𝘁𝗲𝗿 𝗱𝘂𝗿𝗶𝗻𝗴 𝘁𝗵𝗲 𝘄𝗶𝗻𝘁𝗲𝗿. 𝗧𝗵𝗲 𝗼𝗻𝗹𝘆 𝘁𝗵𝗶𝗻𝗴 𝘁𝗵𝗮𝘁 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗶𝘀 𝗽𝘂𝘁𝘁𝗶𝗻𝗴 𝗳𝗼𝗼𝗱 𝗼𝗻 𝘁𝗵𝗲 𝘁𝗮𝗯𝗹𝗲 𝘁𝗼𝗱𝗮𝘆 𝗮𝗻𝗱 𝗲𝘃𝗲𝗿𝘆 𝗱𝗮𝘆.

What are some suggestions from SaaStr for the upcoming period?

How can businesses focus on helping clients achieve real efficiency gains?

What are some strategies for navigating the current downturn in SaaS?

SaaS sector for 2024 and steps to increase revenue

According to the latest IEA Global EV Outlook, more than one in five cars sold worldwide this year will be electric. The newest Outlook, released today, predicts 17 million global electric car sales in 2024. Sales rose 25% in the first quarter compared to 2023, similar to the growth rate a year earlier but on a higher base. The number of electric automobiles sold worldwide in the first three months of this year is comparable to 2020.

Electric car sales in China are expected to reach 10 million in 2024, accounting for 45% of all car sales. In the US, one in nine cars sold will be electric, while in Europe, one in four vehicles sold will be electric, despite a dismal passenger car sales prognosis and the phase-out of subsidies in several countries. This increase followed a record in 2023. Nearly 14 million electric cars were sold worldwide last year, up 35%. While China, Europe, and the US dominate the demand, electric vehicles also grew in emerging markets like Vietnam and Thailand, where 15% and 10% of cars sold were electric.

In the coming years, substantial investment in the electric vehicle supply chain, legislative assistance, and falling #EV and #battery prices will cause even more changes. The Outlook shows that every other #car sold globally will be #electric by 2035 under current policies. By 2035, two in three automobiles sold will be electric if countries meet their energy and climate targets. In this scenario, the quick adoption of electric cars, vans, trucks, buses, and two- and three-wheelers saves 12 million barrels of oil daily, equivalent to China and Europe's road transport needs. The full report can be found here: https://buff.ly/3U8YHjr

What are the latest headlines from China regarding electric car sales?

How can legislative assistance help increase electric car sales?

What are some key strategies for increasing electric car sales?

The world’s electric car fleet continues to grow strongly, with 2024 sales set to reach 17 million

𝗔𝗜 𝘄𝗶𝗹𝗹 (𝘀𝗼𝗼𝗻𝗲𝗿 𝘁𝗵𝗮𝗻 𝗹𝗮𝘁𝗲𝗿) 𝗻𝗲𝗲𝗱 𝘁𝗼 𝗰𝗼𝗻𝘀𝘂𝗺𝗲 𝗲𝗹𝗲𝗰𝘁𝗿𝗶𝗰𝗮𝗹 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝘁𝗵𝗲 𝘀𝗶𝘇𝗲 𝗼𝗳 𝗮𝗻 𝗮𝘃𝗲𝗿𝗮𝗴𝗲 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗲𝗱 𝗻𝗮𝘁𝗶𝗼𝗻. 𝗦𝗼, 𝘄𝗵𝗮𝘁 𝗮𝗿𝗲 𝘄𝗲 𝗱𝗼𝗶𝗻𝗴 𝗮𝗯𝗼𝘂𝘁 𝗶𝘁? 

A.I. workloads are spreading quickly to the network edge, driving up demand for even more processing power, which both established and startup chipmakers are scrambling to supply. The edge will become the primary A.I. workload resource as its importance grows.
 
Studies show that by 2026, #machinelearning and #artificialintelligence (#AI) will be incorporated into 50% of edge computing deployments, up from 5%. In 2022, data centers—which power all computers, including those running Google's search engine and Amazon's #cloud services—consumed between 1% and 1.3 percent of the world's #electricity. That does not include the 0.4 percent used for mining cryptocurrencies. However, some resources are being redistributed to run A.I. By 2030, #datacenter #energy consumption may top 35 gigawatts in the United States alone. It would be sufficient to power about 26 million homes. Another prediction states that by 2027, A.I. servers globally may consume as much energy as Argentina, the Netherlands, or Sweden.
 
According to Gartner's prediction, 75% of the data will be created and processed at the edge by the following year. Bringing A.I. to the #edgecomputing will speed up data processing. It will eliminate the need to transfer data to the cloud for processing, which can take several seconds, and provide strong computing capabilities to the various IoT devices and sensors. When considering use cases such as autonomous vehicles (#EV), processing it at the edge can reduce that time to milliseconds. It also eliminates the cost of processing the data in the cloud and the bandwidth associated with moving it to the cloud. Benefits include data security and compliance: data is less susceptible to errors or attacks when not sent to another location.
 
During the past month, silicon #chip vendors and #semiconductor companies have released new #CPUs, accelerators, and platforms intended to meet the demands of a limited computing environment in many ways. These products address power, analytical processes, and security requirements. Nevertheless, the race is on for #chipmakers, as the primary requirement is to bring all these capabilities close to the locations where massive amounts of data are generated.

How will edge computing benefit data processing?

What is the potential impact of A.I. on edge computing?

What is Gartner's prediction for data processing at the edge?

Energy consumption of artificial intelligence ahead

Wing, a venture capital firm, has compiled the latest Enterprise Tech 30 list, which shows that AI companies are the dominant players among this year's top startups focused on selling technology to businesses.

For the past two years, companies have been making significant investments in #generativeAI, but it's unclear how much of an impact the technology will have on profitability or productivity. This year's ET30 represents the firms developing #GenAI infrastructure, tools, and core model technologies.

Based on the numbers, of the 40 companies on the list, 10 are in the early, mid, or late stages, and 10 are large enterprises. This year's list includes 17 new companies in the ET30. Three of the 17 newly formed companies deal with data platforms or business intelligence, four with software-as-a-service, and seven with AI models and tools.

AI models and tools account for 30% of the ET30 2024 companies, followed by #SaaS at 25%, #data platforms and/or #businessintelligence at 20%, #cybersecurity at 10%, developer tools at 5%, #fintech at 5%, and defense/aerospace at 5%. A broader mix of companies comprises late-stage and large enterprises, but #AI companies predominate the early-stage group.

What is generative AI and how will it impact profitability and productivity?

How are data platforms and/or business intelligence represented on the ET30 list?

What is the Enterprise Tech 30 list and what does it represent?

Enterprise 30 Tech 2024 AI

𝗜𝘀 𝘁𝗵𝗲 𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲-𝗮𝘀-𝗮-𝗦𝗲𝗿𝘃𝗶𝗰𝗲 (𝗦𝗮𝗮𝗦) 𝘀𝗲𝗰𝘁𝗼𝗿 𝗲𝘃𝗼𝗹𝘃𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗮... 𝗦𝗮𝗮𝗦 (𝗦𝗲𝗿𝘃𝗶𝗰𝗲-𝗮𝘀-𝗮-𝗦𝗼𝗳𝘁𝘄𝗮𝗿𝗲) 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗺𝗼𝗱𝗲𝗹 𝗱𝘂𝗲 𝘁𝗼 𝗮𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲? 
𝗜𝘀 𝘁𝗵𝗲 𝗹𝗼𝗻𝗴-𝘁𝗲𝗿𝗺 𝗶𝗺𝗽𝗮𝗰𝘁 𝗼𝗳 𝗔𝗜 𝗶𝗻 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝘀𝗼𝗳𝘁𝘄𝗮𝗿𝗲 𝘂𝗻𝗱𝗲𝗿𝘃𝗮𝗹𝘂𝗲𝗱, 𝗮𝗻𝗱 𝗮𝗿𝗲 𝘁𝗵𝗲 𝘀𝗵𝗼𝗿𝘁-𝘁𝗲𝗿𝗺 𝗴𝗮𝗶𝗻𝘀 𝗯𝗲𝗶𝗻𝗴 𝗼𝘃𝗲𝗿𝗵𝘆𝗽𝗲𝗱?

Short-term pains:
GenAI, despite its promising potential, has yet to gain significant traction in the business world. The primary hurdles are its high cost, the complexities of training, and errors (a.k.a. "hallucinations"). Currently, only large tech companies can afford the technical expertise necessary to develop AI software at a cost-effective scale or integrate AI with their proprietary data for customized tasks. 

Consequently, #GenAI startup businesses need help generating income and transitioning their short-term business model to one that offers consulting as a service. Rather than providing tools to enable self-service, these firms adopt a more proactive approach. They frequently examine their clients' data to identify gaps and then generate data to fill them. Even large enterprise #software companies offer consulting-like services. For example, in November last year, #OpenAI launched its "Custom Model" program to assist clients in training models for specific areas. It may not be as "sexy" as most companies would like, but it still pays the bills in the short term and allows these startups to reconsider their long-term strategies and revenue streams.

Long-term potentials:
SaaS has aided businesses in streamlining their daily operations and processes for the last twenty years. Thanks to #AI, we are entering a new era when things get exponentially more complex and efficiency advances. Software is used not only to digitize and enhance human work, tasks, and services, but in automation 2.0, bots are now far more than just the execution arm of workflows but also the actual brain behind them. The software does not end with workflow organization; agents are also capable of complicated decision-making and autonomy. It completely changes how a task is carried out, with humans still responsible for designing the workflows. 

Ultimately, in any industry, an AI-driven #startup has the potential to rival or even replace a market leader in #SaaS, or it might present an alternative that can coexist with it. In this potential new model, enterprise software companies may charge their clients for access to their platform or tool, but it is still their responsibility to use it to accomplish their goals. The benefit of this shift is a massive market (valued at slightly less than $5 trillion), as the global services market is far more significant than the software market. In the future business world, services will no longer only be provided as software; they will continuously grow and change with us.

What are the key strategies for success in the SaaS industry?

What impact will AI have on the SaaS industry?

How can AI-driven startups reshape the business landscape?

𝙃𝙤𝙬 𝙙𝙤 𝙮𝙤𝙪 𝙣𝙖𝙫𝙞𝙜𝙖𝙩𝙚 𝙖 𝙘𝙤𝙣𝙛𝙡𝙞𝙘𝙩 𝙖𝙩 𝙩𝙝𝙚 𝙩𝙤𝙥 𝙤𝙛 𝙩𝙝𝙚 𝙛𝙤𝙤𝙙 𝙘𝙝𝙖𝙞𝙣 𝙬𝙝𝙚𝙣 𝙮𝙤𝙪 𝙝𝙖𝙫𝙚 𝙖 𝙙𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩 𝙖𝙥𝙥𝙧𝙤𝙖𝙘𝙝 𝙩𝙤 𝙩𝙝𝙚 𝙘𝙤𝙢𝙥𝙖𝙣𝙮'𝙨 𝙨𝙩𝙧𝙖𝙩𝙚𝙜𝙮? 𝘼 𝙦𝙪𝙞𝙘𝙠 𝙥𝙞𝙚𝙘𝙚 𝙤𝙛 𝙖𝙙𝙫𝙞𝙘𝙚 𝙗𝙖𝙨𝙚𝙙 𝙤𝙣 𝙡𝙚𝙨𝙨𝙤𝙣𝙨 𝙡𝙚𝙖𝙧𝙣𝙚𝙙:

First and foremost, understand your point of view about the strategy in detail based on both 1. data (study it repeatedly) and 2. experience and expertise.

There are many terrible managers in the world. These are not incompetent people, but they also lack emotional intelligence. Their lack of awareness is startling. They have no idea how to read people, no emotional self-control, are highly self-preserving (& sometimes self-absorbed), and their morals appear to be on permanent vacation. These leaders are dangerously discordant. They destroy teams and wreck careers. They sometimes overtly and covertly push away good employees. You may discover you are engaged in never-ending, all-consuming battles with these managers.

That said, please ensure you're not inciting conflict with your leader to explain your (lack of) actions, mask your insecurities, or even cover your failures. You must be sincere and fight for causes that benefit everyone, not just yourself. Don't let your morals slide. 

Also, could you avoid (try at least) fighting dirty? One tactic we frequently use in unequal fights (from the beginning of time in every war, conflict, and battle we have as human beings, collectively or individually) is exaggerating or distorting the facts to counterbalance the disadvantage. Backstabbing and sabotage are also reasonably common. It is not healthy for the soul to sink that low.

Losing your job is terrible. Losing yourself in the process & the moral ground (which you perceive as having it) is worse. 
https://buff.ly/4453lnh

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